CN105100098A - Machine card interaction safety authorization method and device - Google Patents

Abstract

Translated fromChinese

本发明的实施例提供一种机卡交互安全授权方法及装置，涉及通信技术领域，能够保证第三方业务APP与SIM卡之间的机卡交互的安全性。该方法包括：获取当前用户的指纹信息；生成当前用户的融合指纹特征向量，融合指纹特征向量包括指纹信息中的至少两个指纹特征的信息；利用第一预设算法，对当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于当前用户的融合指纹特征向量的第一多项式系数向量；利用第二预设算法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数；若相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。

Embodiments of the present invention provide a machine-card interaction security authorization method and device, which relate to the field of communication technology and can ensure the security of machine-card interaction between a third-party service APP and a SIM card. The method includes: acquiring fingerprint information of the current user; generating a fused fingerprint feature vector of the current user, the fused fingerprint feature vector including information of at least two fingerprint features in the fingerprint information; Processing the information of at least two fingerprint features in the feature vector to obtain the first polynomial coefficient vector corresponding to the fusion fingerprint feature vector of the current user; using the second preset algorithm to calculate the first polynomial coefficient vector and the preset The correlation coefficient between the second polynomial coefficient vectors of the fused fingerprint feature vector of the legal user is set; if the correlation coefficient is greater than or equal to the preset threshold, an authorization message is generated to complete the machine-card interaction.

Description

Translated fromChinese

一种机卡交互安全授权方法及装置A method and device for machine-card interaction security authorization

技术领域technical field

本发明涉及通信技术领域，尤其涉及一种机卡交互安全授权方法及装置。The invention relates to the field of communication technology, in particular to a method and device for machine-card interaction security authorization.

背景技术Background technique

随着电信智能卡技术和基于SIM(SubscriberIdentityModule，客户识别模块)卡移动支付业务的不断发展，第三方业务基于电信智能卡技术的产品实现需求日渐增多。第三方业务APP(Application，应用)可通过借助SIM卡实现业务鉴权、身份识别、数据认证等业务功能，从而提高业务安全性、便捷性。With the continuous development of telecom smart card technology and SIM (Subscriber Identity Module, customer identification module) card-based mobile payment services, the demand for third-party business products based on telecom smart card technology is increasing. The third-party business APP (Application, application) can realize business functions such as business authentication, identity recognition, and data authentication by using the SIM card, thereby improving business security and convenience.

目前，第三方业务APP与SIM卡之间的机卡交互是通过SIM卡中存储在固化PKCS#15文件中的访问权限控制文件实现第三方APP与卡之间访问交互。其中，SIM卡中的访问权限控制文件已在运营商营业厅售卡时写入卡中，无法实现远程改写添加新的第三方业务APP的机卡访问权限。At present, the machine-card interaction between the third-party business APP and the SIM card is to realize the access and interaction between the third-party APP and the card through the access control file stored in the solidified PKCS#15 file in the SIM card. Among them, the access rights control file in the SIM card has been written into the card when the card is sold in the business hall of the operator, and it is impossible to remotely rewrite the access rights of the card to add a new third-party service APP.

为解决该问题，业内提出规则控制应用方案代替固化PKCS#15文件中的访问控制权限文件。该方案第三方业务APP与SIM卡之间的机卡交互可以通过卡上的主安全域中访问规则控制应用中的访问规则控制实现，通过OTA(OverTheAir，空中下载)或读卡器等方式对APP业务的机卡访问控制规则进行更新。In order to solve this problem, the industry proposes a rule control application scheme to replace the access control permission file in the hardened PKCS#15 file. In this solution, the machine-card interaction between the third-party service APP and the SIM card can be realized through the access rule control in the access rule control application in the main security domain on the card, through OTA (OverTheAir, over the air download) or card reader, etc. The machine card access control rules for the APP business are updated.

规则控制应用方案可以更好、更灵活地更新第三方业务APP与SIM卡之间的访问控制权限。但是，该方案无法确保第三方业务APP与SIM卡之间的机卡交互访问机制的安全性。如果恶意应用APP或者非法应用获取SIM卡访问权限，则可以通过SIM机卡访问接口，强行访问或窃取卡信息，克隆SIM卡，甚至篡改SIM卡信息，这样，后果将非常严重。The rule control application scheme can better and more flexibly update the access control authority between the third-party business APP and the SIM card. However, this solution cannot ensure the security of the machine-card interactive access mechanism between the third-party service APP and the SIM card. If a malicious app or an illegal app obtains access to the SIM card, it can forcibly access or steal card information through the SIM card access interface, clone the SIM card, or even tamper with the SIM card information. In this way, the consequences will be very serious.

发明内容Contents of the invention

本发明的实施例提供一种机卡交互安全授权方法及装置，解决了目前无法保证第三方业务APP与SIM卡之间的机卡交互的安全性的问题。Embodiments of the present invention provide a method and device for machine-card interaction security authorization, which solves the problem that the security of machine-card interaction between a third-party service APP and a SIM card cannot be guaranteed at present.

为达到上述目的，本发明的实施例采用如下技术方案：In order to achieve the above object, embodiments of the present invention adopt the following technical solutions:

本发明实施例提供一种机卡交互安全授权方法，包括：An embodiment of the present invention provides a machine-card interaction security authorization method, including:

获取当前用户的指纹信息；Obtain the fingerprint information of the current user;

生成当前用户的融合指纹特征向量，所述融合指纹特征向量包括所述指纹信息中的至少两个指纹特征的信息；Generate a fused fingerprint feature vector of the current user, where the fused fingerprint feature vector includes information about at least two fingerprint features in the fingerprint information;

利用第一预设算法，对所述当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于所述当前用户的融合指纹特征向量的第一多项式系数向量；Using a first preset algorithm to process information of at least two fingerprint features in the fused fingerprint feature vector of the current user to obtain a first polynomial coefficient vector corresponding to the fused fingerprint feature vector of the current user;

利用第二预设算法，计算所述第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数；Using a second preset algorithm to calculate the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector of the preset legal user's fused fingerprint feature vector;

若所述相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。If the correlation coefficient is greater than or equal to the preset threshold, an authorization message is generated to complete the machine-card interaction.

所述生成当前用户的融合指纹特征向量，具体包括：Said generating the fusion fingerprint feature vector of the current user specifically includes:

从所述当前用户的指纹信息中提取至少两个指纹特征，并获取当前用户的各个指纹特征的信息，所述指纹特征的信息至少包括所述指纹特征的坐标；Extracting at least two fingerprint features from the fingerprint information of the current user, and obtaining information on each fingerprint feature of the current user, the information on the fingerprint features at least including the coordinates of the fingerprint features;

将所述当前用户的各个指纹特征的坐标组成当前用户的融合指纹特征向量。Composing the coordinates of each fingerprint feature of the current user into a fused fingerprint feature vector of the current user.

所述利用第一预设算法，对所述当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于所述当前用户的融合指纹特征向量的第一多项式系数向量，具体包括：The first preset algorithm is used to process the information of at least two fingerprint features in the fused fingerprint feature vector of the current user to obtain the first polynomial coefficient corresponding to the fused fingerprint feature vector of the current user Vectors, specifically:

利用第一预设算法，将所述当前用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第一多项式曲线解析式；Using a first preset algorithm, fitting the coordinates of each fingerprint feature in the fused fingerprint feature vector of the current user to generate a first polynomial curve analytical formula;

获取所述第一多项曲线解析式的N个系数，其中，所述N≥2；Obtaining N coefficients of the first polynomial curve analytical formula, wherein, the N≥2;

将所述第一多项曲线解析式的N个系数组成第一多项式系数向量。Composing the N coefficients of the first polynomial curve analytical formula into a first polynomial coefficient vector.

生成所述预设的合法用户的融合指纹特征向量的第二多项式系数向量的方法，包括：The method for generating the second polynomial coefficient vector of the fused fingerprint feature vector of the preset legal user includes:

获取合法用户的至少两个指纹信息；Obtain at least two fingerprint information of legitimate users;

生成合法用户的融合指纹特征向量；Generate the fused fingerprint feature vector of the legal user;

利用所述第一预设算法，对所述合法用户的融合指纹特征向量中至少两个指纹特征的信息进行处理，得到对应与所述合法用户的融合指纹特征向量的第二多项式系数向量。Using the first preset algorithm to process the information of at least two fingerprint features in the fused fingerprint feature vector of the legal user to obtain a second polynomial coefficient vector corresponding to the fused fingerprint feature vector of the legal user .

所述生成合法用户的融合指纹特征向量，具体包括：The fusion fingerprint feature vector of described generating legitimate user specifically includes:

从所述合法用户的至少两个指纹信息的每个指纹信息中提取至少两个指纹特征，并获取合法用户的每个指纹信息中各个指纹特征的信息，所述指纹特征的信息至少包括所述指纹特征的坐标；Extract at least two fingerprint features from each of the at least two fingerprint information of the legal user, and obtain information about each fingerprint feature in each fingerprint information of the legal user, where the fingerprint feature information includes at least the Coordinates of fingerprint features;

将所述合法用户的各个指纹特征的坐标组成合法用户的融合指纹特征向量。Combining the coordinates of each fingerprint feature of the legal user into a fused fingerprint feature vector of the legal user.

所述利用所述第一预设算法，对所述合法用户的融合指纹特征向量中至少两个指纹特征的信息进行处理，得到对应与所述合法用户的融合指纹特征向量的第二多项式系数向量，具体包括：The first preset algorithm is used to process the information of at least two fingerprint features in the fused fingerprint feature vector of the legal user to obtain a second polynomial corresponding to the fused fingerprint feature vector of the legal user A vector of coefficients, including:

利用所述第一预设算法，将所述合法用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第二多项式曲线解析式；Using the first preset algorithm, fitting the coordinates of each fingerprint feature in the fused fingerprint feature vector of the legal user to generate a second polynomial curve analytical formula;

获取所述第二多项曲线解析式的N个系数；Obtaining N coefficients of the second polynomial curve analytical formula;

将所述第二多项曲线解析式的N个系数组成第二多项式系数向量。Composing the N coefficients of the second polynomial curve analytical formula into a second polynomial coefficient vector.

本发明实施例提供一种用户设备，所述用户设备包括：An embodiment of the present invention provides a user equipment, where the user equipment includes:

获取单元，用于获取当前用户的指纹信息；an acquisition unit, configured to acquire the fingerprint information of the current user;

处理单元，用于当前用户的融合指纹特征向量，所述融合指纹特征向量包括所述获取单元获取到的所述指纹信息中的至少两个指纹特征的信息，以及用于利用第一预设算法，对所述当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于所述当前用户的融合指纹特征向量的第一多项式系数向量，以及用于利用第二预设算法，计算所述第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数，以及用于若所述相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。The processing unit is used for the fused fingerprint feature vector of the current user, the fused fingerprint feature vector includes information of at least two fingerprint features in the fingerprint information acquired by the acquisition unit, and is used for using the first preset algorithm , processing the information of at least two fingerprint features in the fused fingerprint feature vector of the current user to obtain a first polynomial coefficient vector corresponding to the fused fingerprint feature vector of the current user, and using the second A preset algorithm, calculating the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector, and used if the correlation coefficient is greater than or equal to If the threshold is preset, an authorization message is generated to complete the machine-card interaction.

所述获取单元，具体用于从所述当前用户的指纹信息中提取至少两个指纹特征，以及具体用于获取当前用户的各个指纹特征的信息，所述指纹特征的信息至少包括所述指纹特征的坐标；The acquisition unit is specifically configured to extract at least two fingerprint features from the fingerprint information of the current user, and is specifically used to acquire information on each fingerprint feature of the current user, and the fingerprint feature information includes at least the fingerprint features coordinate of;

所述处理单元，具体用于将所述获取单元获取到的所述当前用户的各个指纹特征的坐标组成当前用户的融合指纹特征向量。The processing unit is specifically configured to compose the coordinates of each fingerprint feature of the current user acquired by the acquiring unit into a fused fingerprint feature vector of the current user.

所述处理单元，具体用于利用第一预设算法，将所述当前用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第一多项式曲线解析式；The processing unit is specifically configured to use a first preset algorithm to fit the coordinates of each fingerprint feature in the fused fingerprint feature vector of the current user to generate a first polynomial curve analytical formula;

所述获取单元，具体用于获取所述第一多项曲线解析式的N个系数，其中，所述N≥2；The acquiring unit is specifically configured to acquire N coefficients of the first polynomial curve analytical formula, where N≥2;

所述处理单元，还具体用于将所述第一多项曲线解析式的N个系数组成第一多项式系数向量。The processing unit is further specifically configured to form the N coefficients of the first polynomial curve analytical expression into a first polynomial coefficient vector.

所述获取单元，还用于获取合法用户的至少两个指纹信息；The obtaining unit is also used to obtain at least two fingerprint information of legal users;

所述处理单元，还用于生成合法用户的融合指纹特征向量，以及还用于利用所述第一预设算法，对所述合法用户的融合指纹特征向量中至少两个指纹特征的信息进行处理，得到对应与所述合法用户的融合指纹特征向量的第二多项式系数向量。The processing unit is further configured to generate a fused fingerprint feature vector of a legitimate user, and is further configured to use the first preset algorithm to process information of at least two fingerprint features in the fused fingerprint feature vector of the legal user , to obtain a second polynomial coefficient vector corresponding to the fused fingerprint feature vector of the legal user.

所述获取单元，具体用于从所述合法用户的至少两个指纹信息的每个指纹信息中提取至少两个指纹特征，以及具体用于获取合法用户的每个指纹信息中各个指纹特征的信息，所述指纹特征的信息至少包括所述指纹特征的坐标；The obtaining unit is specifically used to extract at least two fingerprint features from each of the at least two fingerprint information of the legal user, and is specifically used to obtain information about each fingerprint feature in each fingerprint information of the legal user , the information of the fingerprint features at least includes the coordinates of the fingerprint features;

所述处理单元，具体用于将所述合法用户的各个指纹特征的坐标组成合法用户的融合指纹特征向量。The processing unit is specifically configured to combine the coordinates of each fingerprint feature of the legitimate user into a fused fingerprint feature vector of the legitimate user.

所述处理单元，具体用于利用所述第一预设算法，将所述合法用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第二多项式曲线解析式；The processing unit is specifically configured to use the first preset algorithm to fit the coordinates of each fingerprint feature in the fused fingerprint feature vector of the legal user to generate a second polynomial curve analytical formula;

所述获取单元，具体用于获取所述第二多项曲线解析式的N个系数；The acquiring unit is specifically configured to acquire N coefficients of the second polynomial curve analytical formula;

所述处理单元，还具体用于将所述第二多项曲线解析式的N个系数组成第二多项式系数向量。The processing unit is further specifically configured to form the N coefficients of the second polynomial curve analytical expression into a second polynomial coefficient vector.

本发明实施例提供一种机卡交互安全授权方法及装置，用户设备在获取到当前用户的指纹信息后，根据该指纹信息生成包括当前用户的指纹信息中的至少两个指纹特征信息的融合指纹特征向量，然后，用户设备利用第一预设算法，对当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于当前用户的融合指纹特征向量的第一多项式系数向量，最后，用户设备利用第二预设算法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数，若相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。Embodiments of the present invention provide a method and device for machine-card interaction security authorization. After obtaining the fingerprint information of the current user, the user equipment generates a fusion fingerprint including at least two fingerprint feature information in the fingerprint information of the current user according to the fingerprint information. The feature vector, and then, the user equipment uses the first preset algorithm to process the information of at least two fingerprint features in the current user's fused fingerprint feature vector to obtain the first polynomial corresponding to the current user's fused fingerprint feature vector The coefficient vector. Finally, the user equipment uses the second preset algorithm to calculate the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector. If the correlation coefficient If it is greater than or equal to the preset threshold, an authorization message is generated to complete the machine-card interaction.

通过该方案，用户设备只需对当前用户的身份进行认证，即可根据认证结果确定用户是否授权完成机卡交互，进而保证机卡交互的安全性。用户设备对当前用户的身份进行验证是通过计算当前用户的第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数来完成的。由于当前用户的第一多项式系数向量是对应于当前用户的融合指纹特征向量的，且当前用户的融合指纹特征向量包含了当前用户指纹信息中的至少两个指纹特征信息，因此，利用当前用户的第一多项式系数向量对用户的身份进行认证，能够提高系统的识别精度。当二者之间的相关系数大于或等于预设阈值时，说明当前用户为合法用户，用户设备则生成授权消息，以保证第三方业务APP与SIM卡之间的机卡交互的安全性，达到防止恶意第三方业务APP非法访问SIM卡、攻击SIM卡的目的。Through this solution, the user equipment only needs to authenticate the identity of the current user, and then determine whether the user is authorized to complete the machine-card interaction according to the authentication result, thereby ensuring the security of the machine-card interaction. The user equipment verifies the identity of the current user by calculating the correlation coefficient between the first polynomial coefficient vector of the current user and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector. Since the first polynomial coefficient vector of the current user corresponds to the fused fingerprint feature vector of the current user, and the fused fingerprint feature vector of the current user includes at least two fingerprint feature information in the current user fingerprint information, therefore, using the current The user's first polynomial coefficient vector authenticates the user's identity, which can improve the recognition accuracy of the system. When the correlation coefficient between the two is greater than or equal to the preset threshold, it means that the current user is a legitimate user, and the user equipment generates an authorization message to ensure the security of the machine-card interaction between the third-party service APP and the SIM card, to achieve The purpose of preventing malicious third-party business APP from illegally accessing the SIM card and attacking the SIM card.

附图说明Description of drawings

为了更清楚地说明本发明实施例或现有技术中的技术方案，下面将对实施例或现有技术描述中所需要使用的附图作简单地介绍，显而易见地，下面描述中的附图仅仅是本发明的一些实施例，对于本领域普通技术人员来讲，在不付出创造性劳动的前提下，还可以根据这些附图获得其他的附图。In order to more clearly illustrate the technical solutions in the embodiments of the present invention or the prior art, the following will briefly introduce the drawings that need to be used in the description of the embodiments or the prior art. Obviously, the accompanying drawings in the following description are only These are some embodiments of the present invention. Those skilled in the art can also obtain other drawings based on these drawings without creative work.

图1为本发明实施例的机卡交互安全授权方法流程示意图一；FIG. 1 is a first schematic flow diagram of a machine-card interaction security authorization method according to an embodiment of the present invention;

图2为本发明实施例的机卡交互安全授权方法流程示意图二；FIG. 2 is a second schematic flow diagram of a machine-card interaction security authorization method according to an embodiment of the present invention;

图3本发明实施例的用户设备的结构示意图。Fig. 3 is a schematic structural diagram of a user equipment according to an embodiment of the present invention.

具体实施方式Detailed ways

下面将结合本发明实施例中的附图，对本发明实施例中的技术方案进行清楚、完整地描述，显然，所描述的实施例仅仅是本发明一部分实施例，而不是全部的实施例。基于本发明中的实施例，本领域普通技术人员在没有做出创造性劳动前提下所获得的所有其他实施例，都属于本发明保护的范围。The following will clearly and completely describe the technical solutions in the embodiments of the present invention with reference to the accompanying drawings in the embodiments of the present invention. Obviously, the described embodiments are only some, not all, embodiments of the present invention. Based on the embodiments of the present invention, all other embodiments obtained by persons of ordinary skill in the art without making creative efforts belong to the protection scope of the present invention.

另外，本文中术语“和/或”，仅仅是一种描述关联对象的关联关系，表示可以存在三种关系，例如，A和/或B，可以表示：单独存在A，同时存在A和B，单独存在B这三种情况。另外，本文中字符“/”，一般表示前后关联对象是一种“或”的关系。In addition, the term "and/or" in this article is only an association relationship describing associated objects, which means that there may be three relationships, for example, A and/or B, which may mean: A exists alone, A and B exist at the same time, There are three cases of B alone. In addition, the character "/" in this article generally indicates that the contextual objects are an "or" relationship.

当本发明实施例提及“第一”、“第二”等序数词时，除非根据上下文其确实表达顺序之意，否则应当理解为仅仅是起区分之用。When ordinal numerals such as "first" and "second" are mentioned in the embodiments of the present invention, unless they really express the meaning of order according to the context, it should be understood that they are only used for distinction.

用户设备，可以是能够读取用户指纹信息的无线终端也可以是能够读取用户指纹信息的有线终端，无线终端可以是指向用户提供语音和/或数据连通性的设备，具有无线连接功能的手持式设备、或连接到无线调制解调器的其他处理设备。无线终端可以经无线接入网(例如，RAN，RadioAccessNetwork)与一个或多个核心网进行通信，无线终端可以是移动终端，如移动电话(或称为“蜂窝”电话)和具有移动终端的计算机。User equipment can be a wireless terminal capable of reading user fingerprint information or a wired terminal capable of reading user fingerprint information. The wireless terminal can be a device that provides voice and/or data connectivity to the user, and a handheld device with a wireless connection function. modem, or other processing equipment connected to the wireless modem. The wireless terminal can communicate with one or more core networks via a radio access network (for example, RAN, RadioAccessNetwork), and the wireless terminal can be a mobile terminal, such as a mobile phone (or called a "cellular" phone) and a computer with a mobile terminal .

实施例一Embodiment one

本发明提供一种机卡交互安全授权方法，如图1所示，该方法包括：The present invention provides a machine-card interaction security authorization method, as shown in Figure 1, the method includes:

S101、用户设备获取当前用户的指纹信息。S101. The user equipment acquires fingerprint information of a current user.

S102、用户设备生成当前用户的融合指纹特征向量。S102. The user equipment generates a fused fingerprint feature vector of the current user.

其中，融合指纹特征向量包括指纹信息中的至少两个指纹特征的信息。Wherein, the fused fingerprint feature vector includes information of at least two fingerprint features in the fingerprint information.

为了防止恶意应用第三方业务APP或者非法应用访问SIM卡、攻击SIM卡，用户设备在某个第三方业务APP第一次访问SIM卡时，发起授权请求，请求用户是否授权该第三方业务APP访问SIM卡。具体的，本发明实施例中的用户设备通过采用指纹识别的方法来判断用户是否授权第三方业务APP访问SIM卡，即本发明实施例中的用户设备通过采用指纹识别的方法来判断用户是否授权机卡交互。In order to prevent malicious applications or illegal applications from accessing the SIM card and attacking the SIM card, the user device initiates an authorization request when a third-party service APP accesses the SIM card for the first time, asking whether the user authorizes the third-party service APP to access SIM card. Specifically, the user equipment in the embodiment of the present invention judges whether the user authorizes the third-party service APP to access the SIM card by using the fingerprint identification method, that is, the user equipment in the embodiment of the present invention judges whether the user authorizes the SIM card by using the fingerprint identification method. Machine card interaction.

第三方业务APP是指为了完成某项或某几项特定任务而被开发运行于操作系统之上的计算机程序。本发明实施例中的第三方业务APP为用户设备搭载的系统所兼容的应用程序。A third-party business APP refers to a computer program developed to run on an operating system in order to complete one or several specific tasks. The third-party service APP in the embodiment of the present invention is an application program compatible with the system carried by the user equipment.

优选的，本发明实施例中用户设备搭载的系统为安卓Android操作系统。Preferably, the system carried by the user equipment in the embodiment of the present invention is the Android operating system.

示例性的，用户设备搭载的系统为安卓操作系统，则第三方业务APP为APK(ApplicationPackageFile，应用程序包文件)。Exemplarily, the system carried by the user equipment is an Android operating system, and the third-party service APP is an APK (Application Package File, application program package file).

APK是一种安卓操作系统上的应用程序安装文件格式，一个安卓应用程序的代码在安卓设备上运行，必须先进行编译，然后被打包成为一个被安卓操作系统所能识别的文件才可以被运行，而这种能被安卓操作系统识别并运行的文件格式便是APK。一个APK文件内包含被编译的代码文件(.dex文件)、文件资源(resources)、文件读取(assets)、证书(certificates)和清单文件(manifestfile)。APK is an application installation file format on the Android operating system. The code of an Android application running on an Android device must be compiled first, and then packaged into a file that can be recognized by the Android operating system before it can be run. , and this file format that can be recognized and run by the Android operating system is APK. An APK file contains compiled code files (.dex files), file resources (resources), file reading (assets), certificates (certificates) and manifest files (manifestfile).

具体的，用户设备在接收到某个第三方业务APP第一次请求访问SIM卡的请求消息后，显示提示信息，提示用户输入指纹。在用户设备显示界面提示用户输入指纹后，当前用户根据该提示信息输入指纹，用户设备在当前用户完成输入指纹后，记录该用户的指纹信息。Specifically, after receiving a request message from a third-party service APP requesting to access the SIM card for the first time, the user equipment displays a prompt message to prompt the user to input a fingerprint. After the display interface of the user equipment prompts the user to input the fingerprint, the current user inputs the fingerprint according to the prompt information, and the user equipment records the fingerprint information of the user after the current user finishes inputting the fingerprint.

指纹是人的手指末端正面皮肤上凹凸不平产生的纹线。纹线有规律飞排列成不同的纹型，纹线的起点、终点、结合点和分叉点，称为指纹的细节特征点，即指纹特征。Fingerprints are the uneven lines on the skin on the front of the end of a person's fingers. The lines are regularly arranged into different lines, and the starting point, end point, joint point and bifurcation point of the line are called the detailed feature points of the fingerprint, that is, the fingerprint feature.

指纹特征提供了指纹唯一性的确认信息，包括终结点、分叉点、分歧点、孤立点、环点和短纹等。通常情况下，指纹识别是通过比较不同的指纹特征来进行鉴别的。Fingerprint features provide the confirmation information of the uniqueness of fingerprints, including terminal points, bifurcation points, bifurcation points, isolated points, ring points, and short lines. Typically, fingerprint identification is performed by comparing different fingerprint features for identification.

用户设备在获取到当前用户的指纹信息后，根据当前用户的指纹信息中的至少两个指纹特征，生成当前用户的融合指纹特征向量。After acquiring the fingerprint information of the current user, the user equipment generates a fused fingerprint feature vector of the current user according to at least two fingerprint features in the fingerprint information of the current user.

具体的，用户设备从获取到的当前用户的指纹信息中提取出至少两个指纹特征比如纹线端点、分叉点或短纹等，并获取当前用户的各个指纹特征的坐标，然后将当前用户的各个指纹特征的坐标组成的当前用户的融合指纹特征向量。Specifically, the user device extracts at least two fingerprint features such as ridge endpoints, bifurcation points, or short lines from the acquired fingerprint information of the current user, and obtains the coordinates of each fingerprint feature of the current user, and then the current user The fused fingerprint feature vector of the current user is composed of the coordinates of each fingerprint feature.

需要说明的是，用户设备从指纹信息中提取出指纹特征的方法可以为通过指纹图像分割、图像增强、方向信息提取、脊线提取和图像细化等步骤后将指纹特征提取，也可以为其他方法，本发明实施例对比不做具体限定。It should be noted that the method for the user equipment to extract fingerprint features from fingerprint information may be to extract fingerprint features after steps such as fingerprint image segmentation, image enhancement, direction information extraction, ridge line extraction, and image thinning, or other methods. The method is not specifically limited by the comparison of the examples of the present invention.

示例性的，本发明实施例中的用户设备可以为与网络侧建立有线连接或者无线连接的电子设备，且能够读取用户指纹信息的电子设备，如个人电脑、平板电脑以及智能手机等电子设备。Exemplarily, the user equipment in the embodiment of the present invention may be an electronic device that establishes a wired connection or a wireless connection with the network side and is capable of reading user fingerprint information, such as personal computers, tablet computers, and smart phones. .

S103、用户设备利用第一预设算法，对当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于当前用户的融合指纹特征向量的第一多项式系数向量。S103. The user equipment uses a first preset algorithm to process information of at least two fingerprint features in the fused fingerprint feature vector of the current user to obtain a first polynomial coefficient vector corresponding to the fused fingerprint feature vector of the current user.

具体的，用户设备利用第一预设算法，将当前用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第一多项式曲线解析式，并获取第一多项曲线解析式的N(N≥2)个系数，然后，用户设备将第一多项曲线解析式的N个系数组成第一多项式系数向量。Specifically, the user equipment uses the first preset algorithm to fit the coordinates of each fingerprint feature in the current user's fused fingerprint feature vector to generate the first polynomial curve analytical formula, and obtain the first polynomial curve analytical formula N (N ≥ 2) coefficients of the first polynomial curve analytical expression, and then, the user equipment forms the first polynomial coefficient vector into the N coefficients of the first polynomial curve analytical expression.

其中，本发明实施例中的第一预设算法可以为最小二乘法，也可以为拉格朗日叉乘法，还可以为其他曲线拟合算法，本发明实施例对此不做具体限定。Wherein, the first preset algorithm in the embodiment of the present invention may be the least square method, the Lagrangian cross multiplication method, or other curve fitting algorithms, which are not specifically limited in the embodiment of the present invention.

由于当前用户的第一多项式系数向量是对应于当前用户的融合指纹特征向量的，且当前用户的融合指纹特征向量包含了当前用户指纹信息中的至少两个指纹特征信息，因此，当前用户的第一多项式系数向量也能够用于表明当前用户的身份信息。Since the first polynomial coefficient vector of the current user corresponds to the fused fingerprint feature vector of the current user, and the fused fingerprint feature vector of the current user contains at least two fingerprint feature information in the fingerprint information of the current user, therefore, the current user The first polynomial coefficient vector of can also be used to indicate the identity information of the current user.

S104、用户设备利用第二预设算法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数。S104. The user equipment uses a second preset algorithm to calculate a correlation coefficient between the first polynomial coefficient vector and the preset second polynomial coefficient vector of the fused fingerprint feature vector of the legal user.

用户设备在得到当前用户的第一多项式系数向量后，利用第二预设算法，将该第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量进行相似度计算，获取二者之间的相关系数。After obtaining the first polynomial coefficient vector of the current user, the user equipment uses the second preset algorithm to combine the first polynomial coefficient vector with the second polynomial coefficient of the preset legitimate user's fused fingerprint feature vector Vectors are used to calculate the similarity and obtain the correlation coefficient between the two.

需要说明的是，本发明实施例中的第二预设算法可以为夹角余弦法，也可以为Spearman相关系数法，还可以为广义Jaccard系数法，本发明实施例不做限定。It should be noted that the second preset algorithm in the embodiment of the present invention may be the angle cosine method, the Spearman correlation coefficient method, or the generalized Jaccard coefficient method, which is not limited in this embodiment of the present invention.

其中，本发明实施例中预设的合法用户的融合指纹特征向量的第二多项式系数向量是在合法用户进行注册时生成的，且第二多项式系数向量的生成方法与本发明实施例中当前用户的融合指纹特征向量的第一多项式系数向量的生成方法相同。Wherein, the second polynomial coefficient vector of the fused fingerprint feature vector of the legitimate user preset in the embodiment of the present invention is generated when the legitimate user registers, and the generation method of the second polynomial coefficient vector is the same as that of the present invention. In the example, the generation method of the first polynomial coefficient vector of the fused fingerprint feature vector of the current user is the same.

具体的，本发明实施例中预设的合法用户的融合指纹特征向量的第二多项式系数向量的生成方法为：用户设备获取合法用户的至少两个指纹信息，并根据合法用户的至少两个指纹信息，生成合法用户的融合指纹特征向量，然后，用户设备利用第一预设算法，对合法用户的融合指纹特征向量中至少两个指纹特征的信息进行处理，得到对应与合法用户的融合指纹特征向量的第二多项式系数向量。Specifically, the method for generating the second polynomial coefficient vector of the fused fingerprint feature vector of the legal user preset in the embodiment of the present invention is: the user equipment obtains at least two fingerprint information of the legal user, and according to at least two fingerprint information of the legal user, fingerprint information to generate a legal user's fused fingerprint feature vector, and then, the user equipment uses the first preset algorithm to process the information of at least two fingerprint features in the legal user's fused fingerprint feature vector to obtain the fusion corresponding to the legal user A vector of second polynomial coefficients of the fingerprint feature vector.

同理，用户设备生成合法用户的融合指纹特征向量的过程为：用户设备从合法用户的至少两个指纹信息的每个指纹信息中提取至少两个指纹特征，并获取合法用户的每个指纹信息中各个指纹特征的信息，其中，指纹特征的信息至少包括坐标，然后，将合法用户的各个指纹特征的坐标组成合法用户的融合指纹特征向量。Similarly, the process for the user equipment to generate the fused fingerprint feature vector of the legal user is as follows: the user equipment extracts at least two fingerprint features from each of the at least two fingerprint information of the legal user, and obtains each fingerprint information of the legal user The information of each fingerprint feature, wherein the information of the fingerprint feature at least includes the coordinates, and then, the coordinates of each fingerprint feature of the legitimate user are composed into a fused fingerprint feature vector of the legitimate user.

进一步地，用户设备利用第一预设算法，将合法用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第二多项式曲线解析式，并获取第二多项曲线解析式的N个系数，然后，将第二多项曲线解析式的N个系数组成第二多项式系数向量。Further, the user equipment uses the first preset algorithm to fit the coordinates of each fingerprint feature in the fused fingerprint feature vector of the legal user to generate a second polynomial curve analytical formula, and obtain the second polynomial curve analytical formula Then, the N coefficients of the second polynomial curve analytical expression form a second polynomial coefficient vector.

S105、若相关系数大于或等于预设阈值，用户设备则生成授权消息，以完成机卡交互。S105. If the correlation coefficient is greater than or equal to the preset threshold, the user equipment generates an authorization message to complete the machine-card interaction.

若第一多项式系数向量与第二多项式系数向量之间的相关系数大于或者等于预设阈值，则说明当前用户为合法用户，因此，用户设备生成授权消息，用以机卡交互的顺利进行。If the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector is greater than or equal to the preset threshold, it indicates that the current user is a legitimate user. Therefore, the user equipment generates an authorization message for machine-card interaction. went well.

其中，本发明实施例中的预设阈值可以根据实际应用需求而定，本发明实施例不做限定。Wherein, the preset threshold in the embodiment of the present invention may be determined according to actual application requirements, and is not limited in the embodiment of the present invention.

相应的，若相关系数小于预设阈值，则说明当前用户的指纹信息不被用户设备识别，当前用户有可能为非法用户，因此，用户设备不会生成授权消息，即用户设备阻止此次机卡交互的进行。Correspondingly, if the correlation coefficient is less than the preset threshold, it means that the fingerprint information of the current user is not recognized by the user device, and the current user may be an illegal user. Therefore, the user device will not generate an authorization message, that is, the user device prevents this machine card interactively.

本发明实施例提供一种机卡交互安全授权方法，用户设备在获取到当前用户的指纹信息后，根据该指纹信息生成包括当前用户的指纹信息中的至少两个指纹特征信息的融合指纹特征向量，然后，用户设备利用第一预设算法，对当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于当前用户的融合指纹特征向量的第一多项式系数向量，最后，用户设备利用第二预设算法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数，若相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。An embodiment of the present invention provides a security authorization method for machine-card interaction. After obtaining the fingerprint information of the current user, the user equipment generates a fused fingerprint feature vector including at least two fingerprint feature information in the fingerprint information of the current user according to the fingerprint information. , and then, the user equipment uses the first preset algorithm to process the information of at least two fingerprint features in the fused fingerprint feature vector of the current user to obtain the first polynomial coefficient vector corresponding to the fused fingerprint feature vector of the current user , finally, the user equipment uses the second preset algorithm to calculate the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector, if the correlation coefficient is greater than or is equal to the preset threshold, an authorization message is generated to complete the machine-card interaction.

通过该方案，用户设备只需对当前用户的身份进行认证，即可根据认证结果确定是否授权完成机卡交互，进而保证机卡交互的安全性。用户设备对当前用户的身份进行验证是通过计算当前用户的第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数来完成的。由于当前用户的第一多项式系数向量是对应于当前用户的融合指纹特征向量的，且当前用户的融合指纹特征向量包含了当前用户指纹信息中的至少两个指纹特征信息，因此，利用当前用户的第一多项式系数向量对用户的身份进行认证，能够提高系统的识别精度。当二者之间的相关系数大于或等于预设阈值时，说明当前用户为合法用户，用户设备则生成授权消息，以保证第三方业务APP与SIM卡之间的机卡交互的安全性，达到防止恶意第三方业务APP非法访问SIM卡、攻击SIM卡的目的。Through this solution, the user equipment only needs to authenticate the identity of the current user, and can determine whether to authorize the machine-card interaction according to the authentication result, thereby ensuring the security of the machine-card interaction. The user equipment verifies the identity of the current user by calculating the correlation coefficient between the first polynomial coefficient vector of the current user and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector. Since the first polynomial coefficient vector of the current user corresponds to the fused fingerprint feature vector of the current user, and the fused fingerprint feature vector of the current user includes at least two fingerprint feature information in the current user fingerprint information, therefore, using the current The user's first polynomial coefficient vector authenticates the user's identity, which can improve the recognition accuracy of the system. When the correlation coefficient between the two is greater than or equal to the preset threshold, it means that the current user is a legitimate user, and the user equipment generates an authorization message to ensure the security of the machine-card interaction between the third-party service APP and the SIM card, to achieve The purpose of preventing malicious third-party business APP from illegally accessing the SIM card and attacking the SIM card.

实施例二Embodiment two

本发明提供一种机卡交互安全授权方法，如图2所示，该方法包括：The present invention provides a machine-card interaction security authorization method, as shown in Figure 2, the method includes:

S201、用户设备接收到首次请求访问SIM卡的请求消息。S201. The user equipment receives a request message requesting to access the SIM card for the first time.

具体的，用户设备中的某个第三方业务APP在首次访问SIM卡时，该第三方业务APP会发送请求消息至用户设备的访问控制执行模块。用户设备的访问控制执行模块根据该请求消息发起用户授权请求至用户设备的第一应用程序。Specifically, when a third-party service APP in the user equipment accesses the SIM card for the first time, the third-party service APP will send a request message to the access control execution module of the user equipment. The access control execution module of the user equipment initiates a user authorization request to the first application program of the user equipment according to the request message.

其中，第一应用程序为用户设备自身内置的应用程序，该第一应用程序用于提示用户是否授权机卡交互。Wherein, the first application program is an application program built in the user equipment itself, and the first application program is used to prompt the user whether to authorize the machine-card interaction.

示例性的，本发明实施例中的用户设备可以为与网络侧建立有线连接或者无线连接的电子设备，且能够读取用户指纹信息的电子设备，如个人电脑、平板电脑以及智能手机等电子设备。Exemplarily, the user equipment in the embodiment of the present invention may be an electronic device that establishes a wired connection or a wireless connection with the network side and is capable of reading user fingerprint information, such as personal computers, tablet computers, and smart phones. .

S202、用户设备显示提示信息。S202. The user equipment displays prompt information.

其中，提示信息至少包括用户输入指纹信息的指纹感应区，还可以包括提示用户输入指纹信息的文字，本发明不做限定。Wherein, the prompt information includes at least the fingerprint sensing area for the user to input the fingerprint information, and may also include text prompting the user to input the fingerprint information, which is not limited in the present invention.

具体的，用户设备在接收到首次请求访问SIM卡的请求消息后，用户设备显示界面显示提示信息，提示用户输入指纹，以使得用户通过用户设备输入指纹。Specifically, after the user equipment receives the request message requesting to access the SIM card for the first time, the user equipment display interface displays prompt information, prompting the user to input the fingerprint, so that the user inputs the fingerprint through the user equipment.

例如，用户A在其手机中安装了应用B，应用B在首次访问SIM卡时，会发送首次请求访问SIM卡的请求消息，手机在接收到首次请求访问SIM卡的请求消息后，显示界面会弹出一个窗口，窗口内容为请输入指纹的文字提示和指纹感应区，以便用户A通过指纹感应区输入自己指纹。For example, user A installs application B in his mobile phone. When application B accesses the SIM card for the first time, it will send a request message requesting access to the SIM card for the first time. After the mobile phone receives the request message requesting access to the SIM card for the first time, the display interface will display A window pops up, and the content of the window is the text prompt of please input the fingerprint and the fingerprint sensing area, so that user A can input his own fingerprint through the fingerprint sensing area.

S203、用户设备获取当前用户输入的指纹信息。S203. The user equipment acquires fingerprint information currently input by the user.

在用户设备显示界面显示提示用户输入指纹后，当前用户根据该提示信息输入指纹，用户设备在当前用户完成输入指纹后，记录该用户的指纹信息。After the display interface of the user equipment prompts the user to input the fingerprint, the current user inputs the fingerprint according to the prompt information, and the user equipment records the fingerprint information of the user after the current user finishes inputting the fingerprint.

指纹是人的手指末端正面皮肤上凹凸不平产生的纹线。纹线有规律飞排列成不同的纹型，每个人的指纹携带的信息不同。Fingerprints are the uneven lines on the skin on the front of the end of a person's fingers. The lines are regularly arranged into different patterns, and each person's fingerprints carry different information.

其中，本发明实施例中用户设备获取当前用户的指纹信息可以通过软件采集的方法获取，也可以通过硬件采集的方法获取，本发明实施例不做限定。Wherein, in the embodiment of the present invention, the fingerprint information of the current user acquired by the user equipment may be obtained through a method of software collection, or may be obtained through a method of hardware collection, which is not limited in this embodiment of the present invention.

S204、用户设备从获取到的指纹信息中提取至少两个指纹特征，并获取各个指纹特征的坐标。S204. The user equipment extracts at least two fingerprint features from the acquired fingerprint information, and acquires coordinates of each fingerprint feature.

指纹特征也称为指纹的细节特征点，纹线的起点、终点、结合点和分叉点均为指纹特征。指纹特征提供了指纹唯一性的确认信息，包括终结点、分叉点、分歧点、孤立点、环点和短纹等。通常情况下，指纹识别是通过比较不同的指纹特征来进行鉴别的。The fingerprint feature is also called the detail feature point of the fingerprint, and the starting point, end point, joint point and bifurcation point of the ridge line are all fingerprint features. Fingerprint features provide the confirmation information of the uniqueness of fingerprints, including terminal points, bifurcation points, bifurcation points, isolated points, ring points, and short lines. Typically, fingerprint identification is performed by comparing different fingerprint features for identification.

需要说明的是，从指纹信息中提取出指纹特征的方法可以为通过指纹图像分割、图像增强、方向信息提取、脊线提取和图像细化等步骤后将指纹特征提取，也可以为其他方法，本发明不做限定。It should be noted that the method of extracting fingerprint features from fingerprint information can be fingerprint feature extraction after steps such as fingerprint image segmentation, image enhancement, direction information extraction, ridge line extraction and image thinning, or other methods, The present invention is not limited.

示例性的，用户设备通过指纹图像分割、图像增强、方向信息提取、脊线提取和图像细化后，将原始指纹图像转换成一幅清晰的指纹图像。用户设备获取以当前位置像素为中心的n×n的像素阵列，其中，n大于等于3，将细化后的图像使用n×n的像素阵列用于识别出用户指纹特征的位置与类型。Exemplarily, the user equipment converts the original fingerprint image into a clear fingerprint image after fingerprint image segmentation, image enhancement, direction information extraction, ridge line extraction and image thinning. The user equipment obtains an n×n pixel array centered on the current position pixel, where n is greater than or equal to 3, and uses the n×n pixel array to identify the position and type of the user fingerprint feature in the thinned image.

优选的，本发明实施例中的用户设备选择以当前位置像素为中心的3×3的像素阵列。Preferably, the user equipment in the embodiment of the present invention selects a 3×3 pixel array centered on the pixel at the current position.

表1为3×3区域的像素阵列结构示意图，其中T为当前位置像素点，a₀,a₁,a₂…a₇为周围像素点，像素值已被二值化，即0或1。Table 1 is a schematic diagram of the pixel array structure in a 3×3 area, where T is the current pixel point, a₀ , a₁ , a₂ ... a₇ are surrounding pixel points, and the pixel values have been binarized, that is, 0 or 1.

表13×3区域的像素阵列结构示意图Table 13 Schematic diagram of the pixel array structure in the 3 area

a₈a₈a₁a₁a₂a₂a₇a₇TTa₃a₃a₆a₆a₅a₅a₄a₄

若指纹图像中仅包含有孤立点、末梢点和分叉点，则用户设备从获取到的指纹信息中提取孤立点、末梢点和分叉点三种指纹特征，并获取各个指纹特征的坐标。If the fingerprint image only contains isolated points, terminal points and bifurcation points, the user equipment extracts three fingerprint features of isolated points, terminal points and bifurcation points from the obtained fingerprint information, and obtains the coordinates of each fingerprint feature.

具体的，若T＝1，且则判断为孤立点，记为I_j,j＝1…n₁，其中，n₁为本指纹图像孤立点的个数。Specifically, if T=1, and Then it is judged as an isolated point, which is recorded as I_j ,j=1...n₁ , where n₁ is the number of isolated points in the fingerprint image.

若T＝1，且则判断为脊线末梢点，记为E_k,k＝1…n₂，其中，n₂为本指纹图像末梢点的个数。If T=1, and Then it is judged as the terminal point of the ridge line, recorded as E_k , k=1...n₂ , where n₂ is the number of terminal points of the fingerprint image.

若T＝1，且则判断为分叉点，记为C_k,l＝1…n₃，其中n₃为本指纹图像分叉点的个数。If T=1, and Then it is judged as a bifurcation point, recorded as C_k , l=1...n₃ , where n₃ is the number of bifurcation points in the fingerprint image.

设孤立点的坐标集合为：Let the coordinate set of the isolated point be:

V_I＝{(x_I1,y_I1),(x_I2,y_I2),(x_I3,y_I3),…,(x_In1,y_In1)}(1)V_I ＝{(x_I1 ,y_I1 ),(x_I2 ,y_I2 ),(x_I3 ,y_I3 ),…,(x_In1 ,y_In1 )}(1)

设末梢点的坐标集合为：Let the coordinate set of the terminal point be:

V_E＝{(x_E1,y_E1),(x_E2,y_E2),(x_E3,y_E3),…,(x_En2,y_En2)}(2)V_E ＝{(x_E1 ,y_E1 ),(x_E2 ,y_E2 ),(x_E3 ,y_E3 ),…,(x_En2 ,y_En2 )}(2)

设交叉点的坐标集合为：Let the coordinate set of the intersection point be:

V_C＝{(x_C1,y_C1),(x_C2,y_C2),(x_C3,y_C3),…,(x_Cn3,y_Cn3)}(3)V_C ＝{(x_C1 ,y_C1 ),(x_C2 ,y_C2 ),(x_C3 ,y_C3 ),…,(x_Cn3 ,y_Cn3 )}(3)

S205、用户设备将当前用户的各个指纹特征的坐标组成当前用户的融合指纹特征向量。S205. The user equipment forms the coordinates of each fingerprint feature of the current user into a fused fingerprint feature vector of the current user.

用户设备在获取到当前用户的各个指纹特征的坐标后，将当前用户的各个指纹特征的坐标组合，生成当前用户的融合指纹特征向量。After acquiring the coordinates of each fingerprint feature of the current user, the user equipment combines the coordinates of each fingerprint feature of the current user to generate a fused fingerprint feature vector of the current user.

示例性的，若用户设备获取到孤立点、末梢点和分叉点三种指纹特征的坐标，且这三种指纹特征的坐标分别如公式(1)、(2)和(3)所示，则用户设备将以上三种特征点坐标集合进行串行特征级融合，即得到当前用户的融合特征点向量：Exemplarily, if the user equipment obtains coordinates of three fingerprint features of isolated point, terminal point and bifurcation point, and the coordinates of these three fingerprint features are shown in formulas (1), (2) and (3) respectively, Then the user equipment performs serial feature-level fusion of the above three feature point coordinate sets to obtain the current user's fusion feature point vector:

$\begin{array}{c}{\mathrm{<span><span>V</span>V</span>}}_{\mathrm{<span><span>F</span>f</span>}\mathrm{<span><span>u</span>u</span>}\mathrm{<span><span>s</span>the\; s</span>}\mathrm{<span><span>i</span>i</span>}\mathrm{<span><span>o</span>o</span>}\mathrm{<span><span>n</span>no</span>}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>V</span>V</span>}}_{\mathrm{<span><span>I</span>I</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>V</span>V</span>}}_{\mathrm{<span><span>E</span>E.</span>}}<span><span>,</span>,</span>{\mathrm{<span><span>V</span>V</span>}}_{\mathrm{<span><span>C</span>C</span>}}<span><span>\}</span>\}</span>\\ <span><span>=</span>=</span><span><span>\{</span>\{</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>1</span>1</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>1</span>1</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>2</span>2</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>2</span>2</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>3</span>3</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>3</span>3</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>...</span>...</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{{\mathrm{<span><span>n</span>no</span>}}_{\mathrm{<span><span>2</span>2</span>}}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{{\mathrm{<span><span>n</span>no</span>}}_{\mathrm{<span><span>2</span>2</span>}}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>1</span>1</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>1</span>1</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>2</span>2</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>2</span>2</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>3</span>3</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{\mathrm{<span><span>3</span>3</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>...</span>...</span><span><span>,</span>,</span>\\ <span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{{\mathrm{<span><span>n</span>no</span>}}_{\mathrm{<span><span>2</span>2</span>}}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>E</span>E.</span>}}_{{\mathrm{<span><span>n</span>no</span>}}_{\mathrm{<span><span>2</span>2</span>}}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>C</span>C</span>}}_{\mathrm{<span><span>1</span>1</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>C</span>C</span>}}_{\mathrm{<span><span>1</span>1</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>C</span>C</span>}}_{\mathrm{<span><span>2</span>2</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>C</span>C</span>}}_{\mathrm{<span><span>2</span>2</span>}}}<span><span>)</span>)</span><span><span>,</span>,</span><span><span>(</span>(</span>{\mathrm{<span><span>x</span>x</span>}}_{{\mathrm{<span><span>C</span>C</span>}}_{\mathrm{<span><span>3</span>3</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>y</span>the\; y</span>}}_{{\mathrm{<span><span>C</span>C</span>}}_{\mathrm{<span><span>3</span>3</span>}}}<span><span>)</span>)</span><span><span>\}</span>\}</span>\end{array}<span><span>-</span>-</span><span><span>-</span>-</span><span><span>-</span>-</span><span><span>(</span>(</span>\mathrm{<span><span>4</span>4</span>}<span><span>)</span>)</span>$

S206、用户设备利用第一预设算法，将当前用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第一多项式曲线解析式。S206. The user equipment uses the first preset algorithm to fit the coordinates of each fingerprint feature in the fused fingerprint feature vector of the current user to generate a first polynomial curve analysis formula.

其中，本发明实施例中的第一预设算法可以为最小二乘法，也可以为拉格朗日叉乘法，还可以为其他曲线拟合算法，本发明实施例对此不做具体限定。Wherein, the first preset algorithm in the embodiment of the present invention may be the least square method, the Lagrangian cross multiplication method, or other curve fitting algorithms, which are not specifically limited in the embodiment of the present invention.

示例性的，用户设备应用最小二乘法对当前用户的融合指纹特征向量(5)中的横坐标和纵坐标进行拟合，生成第一多项式曲线解析式：Exemplarily, the user equipment applies the least squares method to fit the abscissa and ordinate in the fused fingerprint feature vector (5) of the current user to generate the first polynomial curve analytical formula:

p(x)＝b₀+b₁x+…+b_n-1x^n-1+b_nxⁿ(6)p(x)＝b₀ +b₁ x+…+b_n-1 x^n-1 +b_n xⁿ (6)

S207、用户设备获取第一多项曲线解析式的N个系数，并将第一多项曲线解析式的N个系数组成第一多项式系数向量，其中，N≥2。S207. The user equipment acquires N coefficients of the first polynomial curve analytical formula, and forms the N coefficients of the first polynomial curve analytical formula into a first polynomial coefficient vector, where N≥2.

示例性的，用户设备生成第一多项式曲线解析式如公式(6)所示，则该用户设备获取公式(6)的系数，并将公式(6)的系数组成第一多项式系数向量：Exemplarily, the user equipment generates the first polynomial curve analytical formula as shown in formula (6), then the user equipment obtains the coefficients of formula (6), and forms the coefficients of formula (6) into the first polynomial coefficients vector:

${\mathrm{<span><span>B</span>B</span>}}_{\mathrm{<span><span>t</span>t</span>}\mathrm{<span><span>e</span>e</span>}\mathrm{<span><span>s</span>the\; s</span>}\mathrm{<span><span>t</span>t</span>}}<span><span>=</span>=</span><span><span>\{</span>\{</span>{\mathrm{<span><span>b</span>b</span>}}_{{\mathrm{<span><span>0</span>0</span>}}_{\mathrm{<span><span>t</span>t</span>}\mathrm{<span><span>e</span>e</span>}\mathrm{<span><span>s</span>the\; s</span>}\mathrm{<span><span>t</span>t</span>}}}<span><span>,</span>,</span>{\mathrm{<span><span>b</span>b</span>}}_{{\mathrm{<span><span>1</span>1</span>}}_{\mathrm{<span><span>t</span>t</span>}\mathrm{<span><span>e</span>e</span>}\mathrm{<span><span>s</span>the\; s</span>}\mathrm{<span><span>t</span>t</span>}}}<span><span>,</span>,</span><span><span>...</span>...</span><span><span>,</span>,</span>{\mathrm{<span><span>b</span>b</span>}}_{{\mathrm{<span><span>n</span>no</span>}}_{\mathrm{<span><span>t</span>t</span>}\mathrm{<span><span>e</span>e</span>}\mathrm{<span><span>s</span>the\; s</span>}\mathrm{<span><span>t</span>t</span>}}}<span><span>\}</span>\}</span><span><span>-</span>-</span><span><span>-</span>-</span><span><span>-</span>-</span><span><span>(</span>(</span>\mathrm{<span><span>7</span>7</span>}<span><span>)</span>)</span>$

由于当前用户的第一多项式系数向量是对应于当前用户的融合指纹特征向量的，且当前用户的融合指纹特征向量包含了当前用户指纹信息中的至少两个指纹特征信息，因此，当前用户的第一多项式系数向量也能够用于表明当前用户的身份信息。Since the first polynomial coefficient vector of the current user corresponds to the fused fingerprint feature vector of the current user, and the fused fingerprint feature vector of the current user contains at least two fingerprint feature information in the fingerprint information of the current user, therefore, the current user The first polynomial coefficient vector of can also be used to indicate the identity information of the current user.

S208、用户设备利用第二预设算法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数。S208. The user equipment calculates the correlation coefficient between the first polynomial coefficient vector and the preset second polynomial coefficient vector of the fused fingerprint feature vector of the legal user by using a second preset algorithm.

其中，本发明实施例中预设的合法用户的融合指纹特征向量的第二多项式系数向量是在合法用户进行注册时生成的，且第二多项式系数向量的生成方法与本发明实施例中当前用户的融合指纹特征向量的第一多项式系数向量的生成方法相同。Wherein, the second polynomial coefficient vector of the fused fingerprint feature vector of the legitimate user preset in the embodiment of the present invention is generated when the legitimate user registers, and the generation method of the second polynomial coefficient vector is the same as that of the present invention. In the example, the generation method of the first polynomial coefficient vector of the fused fingerprint feature vector of the current user is the same.

具体的，本发明实施例中预设的合法用户的融合指纹特征向量的第二多项式系数向量的生成方法为：用户设备获取合法用户的至少两个指纹信息，并根据合法用户的至少两个指纹信息，生成合法用户的融合指纹特征向量，然后，用户设备利用第一预设算法，对合法用户的融合指纹特征向量中至少两个指纹特征的信息进行处理，得到对应与合法用户的融合指纹特征向量的第二多项式系数向量。Specifically, the method for generating the second polynomial coefficient vector of the fused fingerprint feature vector of the legal user preset in the embodiment of the present invention is: the user equipment obtains at least two fingerprint information of the legal user, and according to at least two fingerprint information of the legal user, fingerprint information to generate a legal user's fused fingerprint feature vector, and then, the user equipment uses the first preset algorithm to process the information of at least two fingerprint features in the legal user's fused fingerprint feature vector to obtain the fusion corresponding to the legal user A vector of second polynomial coefficients of the fingerprint feature vector.

同理，用户设备生成合法用户的融合指纹特征向量的过程为：用户设备从合法用户的至少两个指纹信息的每个指纹信息中提取至少两个指纹特征，并获取合法用户的每个指纹信息中各个指纹特征的信息，然后，将合法用户的各个指纹特征的信息组成合法用户的融合指纹特征向量。Similarly, the process for the user equipment to generate the fused fingerprint feature vector of the legal user is as follows: the user equipment extracts at least two fingerprint features from each of the at least two fingerprint information of the legal user, and obtains each fingerprint information of the legal user The information of each fingerprint feature in the legal user, and then, the information of each fingerprint feature of the legitimate user forms the fused fingerprint feature vector of the legitimate user.

进一步地，用户设备利用第一预设算法，将合法用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第二多项式曲线解析式，并获取第二多项曲线解析式的N个系数，然后，将第二多项曲线解析式的N个系数组成第二多项式系数向量。Further, the user equipment uses the first preset algorithm to fit the coordinates of each fingerprint feature in the fused fingerprint feature vector of the legitimate user to generate a second polynomial curve analytical formula, and obtain the second polynomial curve analytical formula Then, the N coefficients of the second polynomial curve analytical expression form a second polynomial coefficient vector.

其中，本发明实施例用代表第二多项式系数向量。Among them, the embodiment of the present invention uses Represents the second polynomial coefficient vector.

具体的，用户设备在得到当前用户的第一多项式系数向量后，利用第二预设算法，将该第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量进行相似度计算，获取二者之间的相关系数。Specifically, after obtaining the first polynomial coefficient vector of the current user, the user equipment uses the second preset algorithm to combine the first polynomial coefficient vector with the second multiplicity of the preset legal user's fused fingerprint feature vector. The term coefficient vector is used to calculate the similarity and obtain the correlation coefficient between the two.

需要说明的是，本发明实施例中的第二预设算法可以为夹角余弦法，也可以为Spearman相关系数法，还可以为广义Jaccard系数法，本发明实施例不做限定。It should be noted that the second preset algorithm in the embodiment of the present invention may be the angle cosine method, the Spearman correlation coefficient method, or the generalized Jaccard coefficient method, which is not limited in this embodiment of the present invention.

示例性的，用户设备利用Spearman相关系数法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数的方法可以为：Exemplarily, the user equipment uses the Spearman correlation coefficient method to calculate the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector of the preset legal user's fused fingerprint feature vector may be:

(1)、用户设备将当前用户的第一多项式系数向量中的各个变量进行排序，生成第三多项式系数向量，并将合法用户的第二多项式系数向量中的各个变量进行排序，生成第四多项式系数向量，其中，预设排序规则为升序规则或降序规则。(1), the user equipment sorts each variable in the first polynomial coefficient vector of the current user, generates a third polynomial coefficient vector, and sorts each variable in the second polynomial coefficient vector of the legal user Sorting to generate a fourth polynomial coefficient vector, wherein the preset sorting rule is an ascending rule or a descending rule.

用户设备将按照升序排列，得到第三多项式系数向量$B_{{\mathrm{test}}^{\&prime;}}=\{b_{0_{{\mathrm{test}}^{\&prime;}}},b_{1_{{\mathrm{test}}^{\&prime;}}},...,b_{n_{{\mathrm{test}}^{\&prime;}}}\},$将$B_{register}=\{b_{0_{register}},b_{1_{register}},...,b_{n_{register}}\}$按照升序排列，得到第四多项式系数向量User equipment will Arranged in ascending order to get the third polynomial coefficient vector$B_{{\mathrm{test}}^{\&prime;}}=\{b_{0_{{\mathrm{test}}^{\&prime;}}},b_{1_{{\mathrm{test}}^{\&prime;}}},...,b_{{\mathrm{no}}_{{\mathrm{test}}^{\&prime;}}}\},$ Will$B_{regi\mathrm{the\; s}ter}=\{b_{0_{regi\mathrm{the\; s}ter}},b_{1_{regi\mathrm{the\; s}ter}},...,b_{{\mathrm{no}}_{regi\mathrm{the\; s}ter}}\}$ Arranged in ascending order, the fourth polynomial coefficient vector is obtained

(2)、用户设备构造一个新向量d_i,i＝1…n，使得d_i保存B_test'与B_register'的差值，即(2), the user equipment constructs a new vector d_i , i=1...n, so that d_i saves the difference between B_test' and B_register' , namely

{d_i＝B_test'-B_register',i＝1…n}(8){d_i ＝B_test' -B_register' ,i＝1...n}(8)

(3)、用户设备计算相似度，将式公式(8)代入公式(9)，(3), the user equipment calculates the similarity, and the formula (8) is substituted into the formula (9),

$\mathrm{<span><span>\&rho;</span>\&rho;</span>}<span><span>=</span>=</span>\mathrm{<span><span>1</span>1</span>}<span><span>-</span>-</span>\frac{\mathrm{<span><span>6</span>6</span>}\mathrm{<span><span>\&Sigma;</span>\&Sigma;</span>}{<span><span>(</span>(</span>{\mathrm{<span><span>B</span>B</span>}}_{{\mathrm{<span><span>test</span>test</span>}}^{<span><span>\&prime;</span>\&prime;</span>}}<span><span>-</span>-</span>{\mathrm{<span><span>B</span>B</span>}}_{{\mathrm{<span><span>register</span>register</span>}}^{<span><span>\&prime;</span>\&prime;</span>}}<span><span>)</span>)</span>}^{\mathrm{<span><span>2</span>2</span>}}}{\mathrm{<span><span>n</span>no</span>}<span><span>(</span>(</span>{\mathrm{<span><span>n</span>no</span>}}^{\mathrm{<span><span>2</span>2</span>}}<span><span>-</span>-</span>\mathrm{<span><span>1</span>1</span>}<span><span>)</span>)</span>}<span><span>-</span>-</span><span><span>-</span>-</span><span><span>-</span>-</span><span><span>(</span>(</span>\mathrm{<span><span>9</span>9</span>}<span><span>)</span>)</span>$

得到:get:

$\mathrm{<span><span>\&rho;</span>\&rho;</span>}<span><span>=</span>=</span>\mathrm{<span><span>1</span>1</span>}<span><span>-</span>-</span>\frac{\mathrm{<span><span>6</span>6</span>}\mathrm{<span><span>\&Sigma;</span>\&Sigma;</span>}{<span><span>(</span>(</span>{\mathrm{<span><span>B</span>B</span>}}_{{\mathrm{<span><span>test</span>test</span>}}^{<span><span>\&prime;</span>\&prime;</span>}}<span><span>-</span>-</span>{\mathrm{<span><span>B</span>B</span>}}_{{\mathrm{<span><span>register</span>register</span>}}^{<span><span>\&prime;</span>\&prime;</span>}}<span><span>)</span>)</span>}^{\mathrm{<span><span>2</span>2</span>}}}{\mathrm{<span><span>n</span>no</span>}<span><span>(</span>(</span>{\mathrm{<span><span>n</span>no</span>}}^{\mathrm{<span><span>2</span>2</span>}}<span><span>-</span>-</span>\mathrm{<span><span>1</span>1</span>}<span><span>)</span>)</span>}<span><span>-</span>-</span><span><span>-</span>-</span><span><span>-</span>-</span><span><span>(</span>(</span>\mathrm{<span><span>10</span>10</span>}<span><span>)</span>)</span>$

其中，相关系数的值ρ∈[0,1]。若计算ρ的值越接近于0，说明相关性越小，则说明当前用户与合法用户的匹配失败；反之，ρ的值接近于1，相关性越大，说明前用户与合法用户的匹配成功。Among them, the value of the correlation coefficient ρ∈[0,1]. If the calculated value of ρ is closer to 0, it means that the correlation is smaller, indicating that the matching between the current user and the legitimate user has failed; otherwise, the value of ρ is close to 1, and the greater the correlation, it means that the previous user and the legitimate user have successfully matched .

S209、若相关系数大于或等于预设阈值，用户设备则生成授权消息，以完成机卡交互。S209. If the correlation coefficient is greater than or equal to the preset threshold, the user equipment generates an authorization message to complete the machine-card interaction.

若第一多项式系数向量与第二多项式系数向量之间的相关系数大于或者等于预设阈值，则说明当前用户为合法用户，因此，用户设备生成授权消息，用以机卡交互的顺利进行。If the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector is greater than or equal to the preset threshold, it indicates that the current user is a legitimate user. Therefore, the user equipment generates an authorization message for machine-card interaction. went well.

其中，本发明实施例中的预设阈值可以根据实际应用需求而定，本发明实施例不做限定。Wherein, the preset threshold in the embodiment of the present invention may be determined according to actual application requirements, and is not limited in the embodiment of the present invention.

相应的，若第一多项式系数向量与第二多项式系数向量之间的相关系数小于预设阈值，则说明当前用户可能为非合法用户，因此，用户设备不会生成授权消息，阻止此次机卡交互。Correspondingly, if the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector is less than the preset threshold, it indicates that the current user may be an illegal user, therefore, the user equipment will not generate an authorization message, preventing This machine card interaction.

本发明实施例提供一种机卡交互安全授权方法，用户设备在获取到当前用户的指纹信息后，根据该指纹信息生成包括当前用户的指纹信息中的至少两个指纹特征信息的融合指纹特征向量，然后，用户设备利用第一预设算法，对当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于当前用户的融合指纹特征向量的第一多项式系数向量，最后，用户设备利用第二预设算法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数，若相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。An embodiment of the present invention provides a security authorization method for machine-card interaction. After obtaining the fingerprint information of the current user, the user equipment generates a fused fingerprint feature vector including at least two fingerprint feature information in the fingerprint information of the current user according to the fingerprint information. , and then, the user equipment uses the first preset algorithm to process the information of at least two fingerprint features in the fused fingerprint feature vector of the current user to obtain the first polynomial coefficient vector corresponding to the fused fingerprint feature vector of the current user , finally, the user equipment uses the second preset algorithm to calculate the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector, if the correlation coefficient is greater than or is equal to the preset threshold, an authorization message is generated to complete the machine-card interaction.

通过该方案，用户设备只需对当前用户的身份进行认证，即可根据认证结果确定是否授权完成机卡交互，进而保证机卡交互的安全性。用户设备对当前用户的身份进行验证是通过计算当前用户的第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数来完成的。由于当前用户的第一多项式系数向量是对应于当前用户的融合指纹特征向量的，且当前用户的融合指纹特征向量包含了当前用户指纹信息中的至少两个指纹特征信息，因此，利用当前用户的第一多项式系数向量对用户的身份进行认证，能够提高系统的识别精度。当二者之间的相关系数大于或等于预设阈值时，说明当前用户为合法用户，用户设备则生成授权消息，以保证第三方业务APP与SIM卡之间的机卡交互的安全性，达到防止恶意第三方业务APP非法访问SIM卡、攻击SIM卡的目的。Through this solution, the user equipment only needs to authenticate the identity of the current user, and can determine whether to authorize the machine-card interaction according to the authentication result, thereby ensuring the security of the machine-card interaction. The user equipment verifies the identity of the current user by calculating the correlation coefficient between the first polynomial coefficient vector of the current user and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector. Since the first polynomial coefficient vector of the current user corresponds to the fused fingerprint feature vector of the current user, and the fused fingerprint feature vector of the current user includes at least two fingerprint feature information in the current user fingerprint information, therefore, using the current The user's first polynomial coefficient vector authenticates the user's identity, which can improve the recognition accuracy of the system. When the correlation coefficient between the two is greater than or equal to the preset threshold, it means that the current user is a legitimate user, and the user equipment generates an authorization message to ensure the security of the machine-card interaction between the third-party service APP and the SIM card, to achieve The purpose of preventing malicious third-party business APP from illegally accessing the SIM card and attacking the SIM card.

实施例三Embodiment three

本发明实施例提供一种用户设备，如图3所示，该用户设备包括：An embodiment of the present invention provides a user equipment. As shown in FIG. 3, the user equipment includes:

获取单元10，用于获取当前用户的指纹信息。The acquiring unit 10 is configured to acquire fingerprint information of the current user.

处理单元11，用于当前用户的融合指纹特征向量，所述融合指纹特征向量包括所述获取单元10获取到的所述指纹信息中的至少两个指纹特征的信息，以及用于利用第一预设算法，对所述当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于所述当前用户的融合指纹特征向量的第一多项式系数向量，以及用于利用第二预设算法，计算所述第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数，以及用于若所述相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。The processing unit 11 is used for the fused fingerprint feature vector of the current user, the fused fingerprint feature vector includes information of at least two fingerprint features in the fingerprint information acquired by the acquisition unit 10, and is used for using the first preset An algorithm is set to process the information of at least two fingerprint features in the fused fingerprint feature vector of the current user to obtain a first polynomial coefficient vector corresponding to the fused fingerprint feature vector of the current user, and to use The second preset algorithm calculates the correlation coefficient between the first polynomial coefficient vector and the second polynomial coefficient vector of the preset legal user's fused fingerprint feature vector, and is used if the correlation coefficient is greater than or is equal to the preset threshold, an authorization message is generated to complete the machine-card interaction.

进一步地，所述获取单元10，具体用于从所述当前用户的指纹信息中提取至少两个指纹特征，以及具体用于获取当前用户的各个指纹特征的信息，所述指纹特征的信息至少包括所述指纹特征的坐标。Further, the acquiring unit 10 is specifically configured to extract at least two fingerprint features from the fingerprint information of the current user, and is specifically used to acquire information about each fingerprint feature of the current user, and the fingerprint feature information includes at least The coordinates of the fingerprint features.

进一步地，所述处理单元11，具体用于将所述获取单元10获取到的所述当前用户的各个指纹特征的坐标组成当前用户的融合指纹特征向量。Further, the processing unit 11 is specifically configured to compose the coordinates of each fingerprint feature of the current user acquired by the acquiring unit 10 into a fused fingerprint feature vector of the current user.

进一步地，所述处理单元10，具体用于利用第一预设算法，将所述当前用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第一多项式曲线解析式。Further, the processing unit 10 is specifically configured to use a first preset algorithm to fit the coordinates of each fingerprint feature in the fused fingerprint feature vector of the current user to generate a first polynomial curve analysis formula.

进一步地，所述获取单元10，具体用于获取所述第一多项曲线解析式的N个系数，其中，所述N≥2。Further, the acquiring unit 10 is specifically configured to acquire N coefficients of the first polynomial curve analytical formula, where N≥2.

进一步地，所述处理单元11，还具体用于将所述第一多项曲线解析式的N个系数组成第一多项式系数向量。Further, the processing unit 11 is also specifically configured to form the N coefficients of the first polynomial curve analytical expression into a first polynomial coefficient vector.

进一步地，所述获取单元10，还用于获取合法用户的至少两个指纹信息。Further, the acquiring unit 10 is also configured to acquire at least two fingerprint information of the legal user.

进一步地，所述处理单元11，还用于生成合法用户的融合指纹特征向量，以及还用于利用所述第一预设算法，对所述合法用户的融合指纹特征向量中至少两个指纹特征的信息进行处理，得到对应与所述合法用户的融合指纹特征向量的第二多项式系数向量。Further, the processing unit 11 is further configured to generate a fused fingerprint feature vector of the legal user, and is also used to perform at least two fingerprint features in the fused fingerprint feature vector of the legal user by using the first preset algorithm. The information is processed to obtain a second polynomial coefficient vector corresponding to the fused fingerprint feature vector of the legal user.

进一步地，所述获取单元10，具体用于从所述合法用户的至少两个指纹信息的每个指纹信息中提取至少两个指纹特征，以及具体用于获取合法用户的每个指纹信息中各个指纹特征的信息，所述指纹特征的信息至少包括所述指纹特征的坐标。Further, the obtaining unit 10 is specifically configured to extract at least two fingerprint features from each of the at least two fingerprint information of the legal user, and is specifically used to obtain each of the fingerprint information of the legal user. Information about fingerprint features, where the information about fingerprint features at least includes coordinates of the fingerprint features.

进一步地，所述处理单元11，具体用于将所述合法用户的各个指纹特征的坐标组成合法用户的融合指纹特征向量。Further, the processing unit 11 is specifically configured to compose the coordinates of each fingerprint feature of the legitimate user into a fused fingerprint feature vector of the legitimate user.

进一步地，所述处理单元11，具体用于利用所述第一预设算法，将所述合法用户的融合指纹特征向量中的各个指纹特征的坐标进行拟合，生成第二多项式曲线解析式。Further, the processing unit 11 is specifically configured to use the first preset algorithm to fit the coordinates of each fingerprint feature in the fused fingerprint feature vector of the legitimate user to generate a second polynomial curve analysis Mode.

进一步地，所述获取单元10，具体用于获取所述第二多项曲线解析式的N个系数。Further, the acquiring unit 10 is specifically configured to acquire N coefficients of the second polynomial curve analytical formula.

进一步地，所述处理单元11，还具体用于将所述第二多项曲线解析式的N个系数组成第二多项式系数向量。Further, the processing unit 11 is also specifically configured to form the N coefficients of the second polynomial curve analytical expression into a second polynomial coefficient vector.

本发明实施例提供一种用户设备，包括获取单元和处理单元。用户设备在获取到当前用户的指纹信息后，根据该指纹信息生成包括当前用户的指纹信息中的至少两个指纹特征信息的融合指纹特征向量，然后，用户设备利用第一预设算法，对当前用户的融合指纹特征向量中的至少两个指纹特征的信息进行处理，得到对应于当前用户的融合指纹特征向量的第一多项式系数向量，最后，用户设备利用第二预设算法，计算第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数，若相关系数大于或等于预设阈值，则生成授权消息，以完成机卡交互。An embodiment of the present invention provides a user equipment, including an acquisition unit and a processing unit. After obtaining the fingerprint information of the current user, the user equipment generates a fusion fingerprint feature vector including at least two fingerprint feature information in the fingerprint information of the current user according to the fingerprint information, and then, the user equipment uses the first preset algorithm to generate The information of at least two fingerprint features in the user's fused fingerprint feature vector is processed to obtain the first polynomial coefficient vector corresponding to the current user's fused fingerprint feature vector. Finally, the user equipment uses the second preset algorithm to calculate the first polynomial coefficient vector. Correlation coefficient between a polynomial coefficient vector and the second polynomial coefficient vector of the fused fingerprint feature vector of the preset legitimate user, if the correlation coefficient is greater than or equal to the preset threshold, an authorization message is generated to complete the machine card interact.

通过该方案，用户设备只需对当前用户的身份进行认证，即可根据认证结果确定是否授权完成机卡交互，进而保证机卡交互的安全性。用户设备对当前用户的身份进行验证是通过计算当前用户的第一多项式系数向量与预设的合法用户的融合指纹特征向量的第二多项式系数向量之间的相关系数来完成的。由于当前用户的第一多项式系数向量是对应于当前用户的融合指纹特征向量的，且当前用户的融合指纹特征向量包含了当前用户指纹信息中的至少两个指纹特征信息，因此，利用当前用户的第一多项式系数向量对用户的身份进行认证，能够提高系统的识别精度。当二者之间的相关系数大于或等于预设阈值时，说明当前用户为合法用户，用户设备则生成授权消息，以保证第三方业务APP与SIM卡之间的机卡交互的安全性，达到防止恶意第三方业务APP非法访问SIM卡、攻击SIM卡的目的。Through this solution, the user equipment only needs to authenticate the identity of the current user, and can determine whether to authorize the machine-card interaction according to the authentication result, thereby ensuring the security of the machine-card interaction. The user equipment verifies the identity of the current user by calculating the correlation coefficient between the first polynomial coefficient vector of the current user and the second polynomial coefficient vector of the preset legitimate user's fused fingerprint feature vector. Since the first polynomial coefficient vector of the current user corresponds to the fused fingerprint feature vector of the current user, and the fused fingerprint feature vector of the current user includes at least two fingerprint feature information in the current user fingerprint information, therefore, using the current The user's first polynomial coefficient vector authenticates the user's identity, which can improve the recognition accuracy of the system. When the correlation coefficient between the two is greater than or equal to the preset threshold, it means that the current user is a legitimate user, and the user equipment generates an authorization message to ensure the security of the machine-card interaction between the third-party service APP and the SIM card, to achieve The purpose of preventing malicious third-party business APP from illegally accessing the SIM card and attacking the SIM card.

所属领域的技术人员可以清楚地了解到，为描述的方便和简洁，仅以上述各功能模块的划分进行举例说明，实际应用中，可以根据需要而将上述功能分配由不同的功能模块完成，即将装置的内部结构划分成不同的功能模块，以完成以上描述的全部或者部分功能。上述描述的系统，装置和单元的具体工作过程，可以参考前述方法实施例中的对应过程，在此不再赘述。Those skilled in the art can clearly understand that for the convenience and brevity of description, only the division of the above-mentioned functional modules is used as an example for illustration. In practical applications, the above-mentioned function allocation can be completed by different functional modules according to needs. The internal structure of the device is divided into different functional modules to complete all or part of the functions described above. For the specific working process of the above-described system, device, and unit, reference may be made to the corresponding process in the foregoing method embodiments, and details are not repeated here.

在本申请所提供的几个实施例中，应该理解到，所揭露的系统，装置和方法，可以通过其它的方式实现。例如，以上所描述的装置实施例仅仅是示意性的，例如，所述模块或单元的划分，仅仅为一种逻辑功能划分，实际实现时可以有另外的划分方式，例如多个单元或组件可以结合或者可以集成到另一个系统，或一些特征可以忽略，或不执行。另一点，所显示或讨论的相互之间的耦合或直接耦合或通信连接可以是通过一些接口，装置或单元的间接耦合或通信连接，可以是电性，机械或其它的形式。In the several embodiments provided in this application, it should be understood that the disclosed system, device and method can be implemented in other ways. For example, the device embodiments described above are only illustrative. For example, the division of the modules or units is only a logical function division. In actual implementation, there may be other division methods. For example, multiple units or components can be Incorporation may either be integrated into another system, or some features may be omitted, or not implemented. In another point, the mutual coupling or direct coupling or communication connection shown or discussed may be through some interfaces, and the indirect coupling or communication connection of devices or units may be in electrical, mechanical or other forms.

以上所述，仅为本发明的具体实施方式，但本发明的保护范围并不局限于此，任何熟悉本技术领域的技术人员在本发明揭露的技术范围内，可轻易想到变化或替换，都应涵盖在本发明的保护范围之内。因此，本发明的保护范围应以所述权利要求的保护范围为准。The above is only a specific embodiment of the present invention, but the scope of protection of the present invention is not limited thereto. Anyone skilled in the art can easily think of changes or substitutions within the technical scope disclosed in the present invention. Should be covered within the protection scope of the present invention. Therefore, the protection scope of the present invention should be determined by the protection scope of the claims.

Claims (12)

1. the mutual security certificate method of machine card, is characterized in that, comprising:

Obtain the finger print information of active user;

Generate the fusion fingerprint characteristic vector of active user, described fusion fingerprint characteristic vector comprises the information of at least two fingerprint characteristics in described finger print information;

Utilize the first preset algorithm, the information of at least two fingerprint characteristics in the fusion fingerprint characteristic vector of described active user is processed, obtain the first system of polynomials number vector of the fusion fingerprint characteristic vector corresponding to described active user;

Utilize the second preset algorithm, the coefficient correlation between the second system of polynomials number vector calculating the fusion fingerprint characteristic vector of described first system of polynomials number vector and default validated user;

If described coefficient correlation is more than or equal to predetermined threshold value, then generate authorization messages, mutual to complete machine card.

2. the mutual security certificate method of machine card according to claim 1, is characterized in that, the fusion fingerprint characteristic vector of described generation active user, specifically comprises:

From the finger print information of described active user, extract at least two fingerprint characteristics, and obtain the information of each fingerprint characteristic of active user, the information of described fingerprint characteristic at least comprises the coordinate of described fingerprint characteristic;

By the fusion fingerprint characteristic vector of the coordinate of each fingerprint characteristic of described active user composition active user.

3. the mutual security certificate method of machine card according to claim 2, it is characterized in that, describedly utilize the first preset algorithm, the information of at least two fingerprint characteristics in the fusion fingerprint characteristic vector of described active user is processed, obtain the first system of polynomials number vector of the fusion fingerprint characteristic vector corresponding to described active user, specifically comprise:

Utilize the first preset algorithm, the coordinate of each fingerprint characteristic in the fusion fingerprint characteristic vector of described active user is carried out matching, generates the first polynomial curve analytic expression;

Obtain N number of coefficient of described first multinomial Curve Resolution formula, wherein, described N >=2;

N number of coefficient of described first multinomial Curve Resolution formula is formed the first system of polynomials number vector.

4. the mutual security certificate method of machine card according to claim 1, is characterized in that, generates the method for the second system of polynomials number vector of the fusion fingerprint characteristic vector of described default validated user, comprising:

Obtain at least two finger print informations of validated user;

Generate the fusion fingerprint characteristic vector of validated user;

Utilize described first preset algorithm, the information of at least two fingerprint characteristics in the fusion fingerprint characteristic vector of described validated user is processed, obtain the second system of polynomials number vector that is corresponding and the fusion fingerprint characteristic vector of described validated user.

5. the mutual security certificate method of machine card according to claim 4, is characterized in that, the fusion fingerprint characteristic vector of described generation validated user, specifically comprises:

At least two fingerprint characteristics are extracted from each finger print information of at least two finger print informations of described validated user, and obtaining the information of each fingerprint characteristic in each finger print information of validated user, the information of described fingerprint characteristic at least comprises the coordinate of described fingerprint characteristic;

By the fusion fingerprint characteristic vector of the coordinate of each fingerprint characteristic of described validated user composition validated user.

6. the mutual security certificate method of machine card according to claim 5, it is characterized in that, describedly utilize described first preset algorithm, the information of at least two fingerprint characteristics in the fusion fingerprint characteristic vector of described validated user is processed, obtain the second system of polynomials number vector that is corresponding and the fusion fingerprint characteristic vector of described validated user, specifically comprise:

Utilize described first preset algorithm, the coordinate of each fingerprint characteristic in the fusion fingerprint characteristic vector of described validated user is carried out matching, generates the second polynomial curve analytic expression;

Obtain N number of coefficient of described second multinomial Curve Resolution formula;

N number of coefficient of described second multinomial Curve Resolution formula is formed the second system of polynomials number vector.

7. a subscriber equipment, is characterized in that, comprising:

Acquiring unit, for obtaining the finger print information of active user;

Processing unit, for the fusion fingerprint characteristic vector of active user, described fusion fingerprint characteristic vector comprises the information of at least two fingerprint characteristics in the described finger print information that described acquiring unit gets, and for utilizing the first preset algorithm, the information of at least two fingerprint characteristics in the fusion fingerprint characteristic vector of described active user is processed, obtain the first system of polynomials number vector of the fusion fingerprint characteristic vector corresponding to described active user, and for utilizing the second preset algorithm, coefficient correlation between the second system of polynomials number vector calculating the fusion fingerprint characteristic vector of described first system of polynomials number vector and default validated user, if and be more than or equal to predetermined threshold value for described coefficient correlation, then generate authorization messages, mutual to complete machine card.

8. subscriber equipment according to claim 7, is characterized in that,

Described acquiring unit, specifically for extracting at least two fingerprint characteristics in the finger print information from described active user, and specifically for obtaining the information of each fingerprint characteristic of active user, the information of described fingerprint characteristic at least comprises the coordinate of described fingerprint characteristic;

Described processing unit, specifically for the fusion fingerprint characteristic vector of the coordinate composition active user of each fingerprint characteristic of described active user got by described acquiring unit.

9. subscriber equipment according to claim 8, is characterized in that,

Described processing unit, specifically for utilizing the first preset algorithm, carrying out matching by the coordinate of each fingerprint characteristic in the fusion fingerprint characteristic vector of described active user, generating the first polynomial curve analytic expression;

Described acquiring unit, specifically for obtaining N number of coefficient of described first multinomial Curve Resolution formula, wherein, described N >=2;

Described processing unit, also specifically for N number of coefficient of described first multinomial Curve Resolution formula is formed the first system of polynomials number vector.

10. subscriber equipment according to claim 7, is characterized in that,

Described acquiring unit, also for obtaining at least two finger print informations of validated user;

Described processing unit, also for generating the fusion fingerprint characteristic vector of validated user, and also for utilizing described first preset algorithm, the information of at least two fingerprint characteristics in the fusion fingerprint characteristic vector of described validated user is processed, obtains the second system of polynomials number vector that is corresponding and the fusion fingerprint characteristic vector of described validated user.

11. subscriber equipmenies according to claim 10, is characterized in that,

Described acquiring unit, specifically for extracting at least two fingerprint characteristics in each finger print information of at least two finger print informations from described validated user, and specifically for obtain validated user each finger print information in the information of each fingerprint characteristic, the information of described fingerprint characteristic at least comprises the coordinate of described fingerprint characteristic;

Described processing unit, specifically for the fusion fingerprint characteristic vector of the coordinate composition validated user of each fingerprint characteristic by described validated user.

12. subscriber equipmenies according to claim 11, is characterized in that,

Described processing unit, specifically for utilizing described first preset algorithm, carrying out matching by the coordinate of each fingerprint characteristic in the fusion fingerprint characteristic vector of described validated user, generating the second polynomial curve analytic expression;

Described acquiring unit, specifically for obtaining N number of coefficient of described second multinomial Curve Resolution formula;

Described processing unit, also specifically for N number of coefficient of described second multinomial Curve Resolution formula is formed the second system of polynomials number vector.