技术领域technical field
本发明涉及辅助身份验证方法，更具体地，涉及基于用户网络行为特征的辅助身份验证方法。The invention relates to an auxiliary identity verification method, and more specifically, to an auxiliary identity verification method based on user network behavior characteristics.
背景技术Background technique
目前，随着计算机和网络应用的日益广泛以及不同领域的业务种类的日益丰富，在常规的主验证过程（例如基于用户名和密码的验证方式）之外对网络用户进行辅助身份验证变得越来越重要。At present, with the increasingly wide application of computers and networks and the increasing variety of businesses in different fields, it is becoming more and more important to perform secondary identity verification on network users in addition to the conventional main verification process (such as verification methods based on user names and passwords). more important.
现有的辅助身份验证方法通常借助手机短信（即在主验证通过之后向用户发送短信，用户随之基于该短信传送回响应信息，由此辅助确定用户的身份）或者生物识别（例如基于用户的指纹、虹膜、语音等等辅助确定用户的身份）而实现，。Existing auxiliary identity verification methods usually rely on mobile phone text messages (that is, after the main verification is passed, a short message is sent to the user, and the user then sends back a response information based on the short message, thereby assisting in determining the user's identity) or biometrics (such as based on the user's fingerprint, iris, voice, etc. to assist in determining the identity of the user).
然而，现有的技术方案存在如下问题：（1）短信验证的方式需要用户随身携带手机并且所处的环境具有良好的无线通信信息，因而适用性较差，并且如果发生短信接收延迟会导致用户响应延误而失去时效的情况；（2）生物识别的方式需要附加的特定硬件和软件设施，故成本较高且适用面较窄。However, the existing technical solutions have the following problems: (1) The SMS verification method requires the user to carry a mobile phone and the environment has good wireless communication information, so the applicability is poor, and if a delay in receiving the SMS occurs, it will cause the user The situation of losing timeliness due to delay in response; (2) The biometric method requires additional specific hardware and software facilities, so the cost is high and the scope of application is narrow.
因此，存在如下需求：提供适用性广泛、便捷有效并且成本较低的基于用户网络行为特征的辅助身份验证方法。Therefore, there is a need to provide a widely applicable, convenient, effective and low-cost auxiliary authentication method based on user network behavior characteristics.
发明内容Contents of the invention
为了解决上述现有技术方案所存在的问题，本发明提出了适用性广泛、便捷有效并且成本较低的基于用户网络行为特征的辅助身份验证方法。In order to solve the problems in the above existing technical solutions, the present invention proposes a widely applicable, convenient, effective and low-cost auxiliary identity verification method based on user network behavior characteristics.
本发明的目的是通过以下技术方案实现的：The purpose of the present invention is achieved through the following technical solutions:
一种辅助身份验证方法，所述辅助身份验证方法包括下列步骤：An auxiliary identity verification method, said auxiliary identity verification method comprising the following steps:
（A1）收集并分析社交网站账户数据以得到训练数据集，并随之构建用户识别模型以及将所述训练数据集作为输入训练所述用户识别模型，以使其能够正常工作；(A1) Collect and analyze social networking site account data to obtain a training data set, and then construct a user identification model and use the training data set as input to train the user identification model so that it can work normally;
（A2）当用户意图进行与数据处理服务器之间的实际数据交互过程之前，所述数据处理服务器以常规的方式执行针对该用户的主身份验证过程，并且如果所述主身份验证过程的结果是“通过”，则向与其相关联的验证服务器发送辅助验证请求以触发辅助身份验证过程，并仅在辅助身份验证结果为“通过”的情况下允许该用户进行后续的实际数据交互过程；(A2) before the user intends to proceed with the actual data interaction process with the data processing server, said data processing server performs a main authentication process for the user in a conventional manner, and if the result of said main authentication process is "Pass", then send a secondary verification request to its associated verification server to trigger the secondary authentication process, and allow the user to proceed with the subsequent actual data interaction process only if the secondary authentication result is "passed";
（A3）所述辅助验证服务器基于运行于其上的所述用户识别模型执行针对该用户的辅助身份验证过程，并将辅助身份验证结果传送回所述数据处理服务器。(A3) The auxiliary authentication server performs an auxiliary authentication process for the user based on the user identification model running on it, and transmits an auxiliary authentication result back to the data processing server.
在上面所公开的方案中，优选地，分析社交网站账户数据包括：（1）人工判断并标示每个社交网站账户的类别从而将各个社交网站账户分别归类为“正常账号”或“垃圾账号”；（2）从社交网站账户数据中抽取出使用所述社交网站账户的各个用户的特定的特征属性以形成训练数据。In the solution disclosed above, preferably, analyzing the social networking site account data includes: (1) manually judging and marking the category of each social networking site account so as to classify each social networking site account as "normal account" or "junk account"; ”; (2) extracting specific characteristic attributes of each user using the social networking site account from the social networking site account data to form training data.
在上面所公开的方案中，优选地，基于分类器模式构建所述用户识别模型，并基于机器学习算法训练所述用户识别模型，其中，所述用户识别模型通过量化用户的所述特征属性并将其与预定的一个或多个阈值相比较来实际验证用户身份。In the solution disclosed above, preferably, the user identification model is constructed based on a classifier model, and the user identification model is trained based on a machine learning algorithm, wherein the user identification model quantifies the user's characteristic attributes and This is compared to one or more predetermined thresholds to actually authenticate the user.
在上面所公开的方案中，优选地，所述特征属性包括用户的基本信息、社交信息以及社交行为信息。In the solutions disclosed above, preferably, the characteristic attributes include the user's basic information, social information and social behavior information.
在上面所公开的方案中，优选地，所述辅助验证请求包含用户的用于主身份验证过程的第一用户标识符。In the solution disclosed above, preferably, the secondary authentication request contains the user's first user identifier for the primary authentication process.
在上面所公开的方案中，优选地，所述步骤（A3）进一步包括：（1）在接收到所述辅助验证请求后，所述验证服务器通过特定的用户界面提示用户登录特定的社交网站以获得与该用户相关联的社交网站账户数据，其中，所述用户使用第二用户标识符登录所述社交网站；（2）如果登录操作失败，则所述验证服务器提示用户“登录失败，无法验证”并向所述数据处理服务器返回指示“无法验证”的验证结果，如果所述登录操作成功，则进入步骤（3）；（3）通过查询验证历史纪录数据库确定当前登录是否是该用户的首次登录，并且如果是首次登录，则将所述第一用户标识符与所述第二用户标识符相关联并将关联关系纪录在所述验证历史纪录数据库中并进入步骤（5），如果不是首次登录，则通过查询所述验证历史纪录数据库确定所述第二用户标识符是否与之前与所述第一用户标识符相关联的验证纪录中所指示的关联标识符相一致，如果不一致，则终止验证过程并向所述数据处理服务器返回指示“验证失败”的验证结果，如果一致，进入步骤（4）；（4）确定与所述第二用户标识符相关的最近一次成功验证的时间与当前时间的时间差，如果该时间差不超过预定的阈值，则终止验证过程并向所述数据处理服务器返回指示“验证成功”的验证结果，如果该时间差超过预定的阈值，则进入步骤（5）；（5）获取与该用户相关联的社交网站账户数据并抽取出该用户的所述特征属性，随之通过该用户识别模型计算该账户被分类为“正常账号”的概率值，随之将该概率值与预定的阈值相比较并计算该账户的注册时间与当前时间的时间差，如果该概率值不超过所述预定的阈值并且所述时间差不超过预定的时间阈值，则在所述验证历史纪录数据库中纪录该账户的本次验证的验证时间、账户信息和验证结果并终止验证过程以及向所述数据处理服务器返回指示“验证成功”的验证结果，否则，终止验证过程以及向所述数据处理服务器返回指示“验证失败”的验证结果。In the solution disclosed above, preferably, the step (A3) further includes: (1) After receiving the auxiliary verification request, the verification server prompts the user to log in to a specific social networking site through a specific user interface to Obtain the social networking site account data associated with the user, wherein the user uses the second user identifier to log in to the social networking site; (2) if the login operation fails, the verification server prompts the user "login failed, unable to verify " and return a verification result indicating "unable to verify" to the data processing server, and if the login operation is successful, proceed to step (3); (3) determine whether the current login is the user's first time by querying the verification history database log in, and if it is the first time to log in, associate the first user identifier with the second user identifier and record the association relationship in the verification history record database and enter step (5), if it is not the first time log in, determine whether the second user identifier is consistent with the associated identifier indicated in the verification record previously associated with the first user identifier by querying the verification history database, and if not, terminate During the verification process, return the verification result indicating "verification failure" to the data processing server. If they are consistent, go to step (4); (4) determine that the time of the latest successful verification related to the second user identifier is the same as the current time difference, if the time difference does not exceed the predetermined threshold, the verification process is terminated and a verification result indicating "verification successful" is returned to the data processing server, if the time difference exceeds the predetermined threshold, then enter step (5); ( 5) Obtain the social networking site account data associated with the user and extract the characteristic attributes of the user, then calculate the probability value of the account being classified as a "normal account" through the user identification model, and then use the probability value value is compared with a predetermined threshold and calculates the time difference between the registration time of the account and the current time, if the probability value does not exceed the predetermined threshold and the time difference does not exceed the predetermined time threshold, then in the verification history database Record the verification time, account information and verification result of the account in this verification and terminate the verification process and return the verification result indicating "verification successful" to the data processing server; otherwise, terminate the verification process and report to the data processing server Returns a validation result indicating "Verification Failed".
在上面所公开的方案中，优选地，所述步骤（A3）进一步包括：如果验证失败的原因是注册时间与当前时间的时间差小于所述时间阈值，则提示用户“账号注册时间太短”。In the solution disclosed above, preferably, the step (A3) further includes: if the reason for verification failure is that the time difference between the registration time and the current time is less than the time threshold, prompting the user that "account registration time is too short".
本发明所公开的基于用户网络行为特征的辅助身份验证方法具有以下优点：具有广泛的适用性、并且便捷有效且成本较低。The auxiliary identity verification method based on user network behavior characteristics disclosed by the present invention has the following advantages: it has wide applicability, is convenient, effective and low in cost.
附图说明Description of drawings
结合附图，本发明的技术特征以及优点将会被本领域技术人员更好地理解，其中：With reference to the accompanying drawings, the technical features and advantages of the present invention will be better understood by those skilled in the art, wherein:
图1是根据本发明的实施例的辅助身份验证方法的流程图。Fig. 1 is a flow chart of an auxiliary identity verification method according to an embodiment of the present invention.
具体实施方式detailed description
图1是根据本发明的实施例的辅助身份验证方法的流程图。如图1所示，本发明所公开的辅助身份验证方法包括下列步骤：（A1）收集并分析社交网站（例如微博网站等等）账户数据以得到训练数据集，并随之构建用户识别模型以及将所述训练数据集作为输入训练所述用户识别模型，以使其能够正常工作；（A2）当用户意图进行与数据处理服务器（例如服务提供方服务器）之间的实际数据交互过程之前，所述数据处理服务器以常规的方式执行针对该用户的主身份验证过程，并且如果所述主身份验证过程的结果是“通过”，则向与其相关联的验证服务器发送辅助验证请求以触发辅助身份验证过程，并仅在辅助身份验证结果为“通过”的情况下允许该用户进行后续的实际数据交互过程；（A3）所述辅助验证服务器基于运行于其上的所述用户识别模型执行针对该用户的辅助身份验证过程，并将辅助身份验证结果传送回所述数据处理服务器。Fig. 1 is a flow chart of an auxiliary identity verification method according to an embodiment of the present invention. As shown in Figure 1, the auxiliary identity verification method disclosed in the present invention includes the following steps: (A1) collect and analyze social networking site (such as microblogging sites, etc.) account data to obtain a training data set, and then build a user identification model and using the training data set as input to train the user recognition model so that it can work normally; (A2) before the user intends to perform the actual data interaction process with the data processing server (such as the server of the service provider), The data processing server performs the primary authentication process for the user in a conventional manner, and if the result of the primary authentication process is "pass", sends a secondary authentication request to its associated authentication server to trigger the secondary authentication verification process, and allow the user to proceed with the subsequent actual data interaction process only if the auxiliary identity verification result is "pass"; (A3) the auxiliary verification server executes the authentication for the user based on the user identification model running on it The user's secondary authentication process, and the secondary authentication result is transmitted back to the data processing server.
优选地，在本发明所公开的辅助身份验证方法中，分析社交网站账户数据包括：（1）人工判断并标示每个社交网站账户的类别从而将各个社交网站账户分别归类为“正常账号”或“垃圾账号”；（2）从社交网站账户数据中抽取出使用所述社交网站账户的各个用户的特定的特征属性以形成训练数据。Preferably, in the auxiliary identity verification method disclosed in the present invention, analyzing social networking site account data includes: (1) manually judging and marking the category of each social networking site account so as to classify each social networking site account as a "normal account" or "junk account"; (2) extracting specific characteristic attributes of each user using the social networking site account from the social networking site account data to form training data.
优选地，在本发明所公开的辅助身份验证方法中，基于分类器模式构建所述用户识别模型，并基于机器学习算法训练所述用户识别模型，其中，所述用户识别模型通过量化用户的所述特征属性并将其与预定的一个或多个阈值相比较来实际验证用户身份。Preferably, in the auxiliary identity verification method disclosed in the present invention, the user identification model is constructed based on a classifier model, and the user identification model is trained based on a machine learning algorithm, wherein the user identification model quantifies the user's The above characteristic attributes are compared to one or more predetermined thresholds to actually authenticate the user.
优选地，在本发明所公开的辅助身份验证方法中，所述训练数据集所包含的“正常账号”和“垃圾账号”的数量基本相等。这可以有效地防止训练数据的倾斜而影响用户识别模型的工作效果。Preferably, in the auxiliary identity verification method disclosed in the present invention, the number of "normal accounts" and "junk accounts" included in the training data set is substantially equal. This can effectively prevent the skew of training data from affecting the working effect of the user recognition model.
优选地，在本发明所公开的辅助身份验证方法中，所述特征属性包括用户的基本信息（例如，地区是否设置、地区设置的值、性别是否设置、性别设置的值、头像是否设置、生日是否设置、生日设置的值、邮箱是否设置、职业信息是否设置、职业经历的次数、教育信息是否设置、教育的次数等等）、社交信息（例如，粉丝数、关注数、以及两者的比例、双向好友的数量、关注者是否进行分组，分组的组数等等）以及社交行为信息（例如，发布博文的数量、一天内平均发文的时间跨度、含有URL的博文比例、博文中其他人的平均数量、类似博文的数量、类似博文的比例、类似博文的平均数量、类似博文的发布平均间隔时间、发布博文的平均评论数等等）。基于这些特征信息，所述用户识别模型能够判断和识别使用该社交网站账户的用户的类型，例如垃圾账号一般会具有下列特征：基本信息较少填写，拥有少量的粉丝，较多的关注者，并且后者数量远多于前者，较少发布博文和评论，或者短时间内传播大量广告、虚假消息。Preferably, in the auxiliary identity verification method disclosed in the present invention, the feature attributes include the user's basic information (for example, whether the region is set, the value of the region setting, whether the gender is set, the value of the gender setting, whether the avatar is set, birthday Whether it is set, the value of birthday setting, whether the mailbox is set, whether the career information is set, the number of career experiences, whether the education information is set, the number of times of education, etc.), social information (for example, the number of fans, the number of followers, and the ratio of the two , the number of two-way friends, whether followers are grouped, the number of groups, etc.) and social behavior information (for example, the number of blog posts, the average time span of posting in a day, the proportion of blog posts containing URLs, the number of other people in blog posts Average number, number of similar posts, proportion of similar posts, average number of similar posts, average time between similar posts, average number of comments on published posts, etc.). Based on these feature information, the user identification model can judge and identify the type of user using the social networking site account. For example, junk accounts generally have the following characteristics: less basic information to fill in, a small number of fans, more followers, And the number of the latter is far greater than that of the former, and fewer blog posts and comments are published, or a large number of advertisements and false news are spread in a short period of time.
优选地，在本发明所公开的辅助身份验证方法中，所述辅助验证请求包含用户的用于主身份验证过程的第一用户标识符（即用户ID）。Preferably, in the auxiliary identity verification method disclosed in the present invention, the auxiliary verification request includes the user's first user identifier (ie user ID) used in the main identity verification process.
优选地，在本发明所公开的辅助身份验证方法中，所述步骤（A3）进一步包括：（1）在接收到所述辅助验证请求后，所述验证服务器通过特定的用户界面提示用户登录特定的社交网站（例如微博网站，其已对验证服务器进行了授权，使其能够通过用户的登录操作获取相关的社交网站账户数据）以获得与该用户相关联的社交网站账户数据（其由社交网站服务器发送至所述验证服务器），其中，所述用户使用第二用户标识符（即用户的社交网站账户）登录所述社交网站；（2）如果登录操作失败，则所述验证服务器提示用户“登录失败，无法验证”并向所述数据处理服务器返回指示“无法验证”的验证结果，如果所述登录操作成功，则进入步骤（3）；（3）通过查询验证历史纪录数据库确定当前登录是否是该用户的首次登录，并且如果是首次登录，则将所述第一用户标识符与所述第二用户标识符相关联并将关联关系纪录在所述验证历史纪录数据库中并进入步骤（5），如果不是首次登录，则通过查询所述验证历史纪录数据库确定所述第二用户标识符是否与之前与所述第一用户标识符相关联的验证纪录（即之前纪录的与所述第一用户标识符相关的关联关系）中所指示的关联标识符相一致，如果不一致，则终止验证过程并向所述数据处理服务器返回指示“验证失败”的验证结果，如果一致，进入步骤（4）；（4）确定与所述第二用户标识符相关的最近一次成功验证的时间与当前时间的时间差，如果该时间差不超过预定的阈值，则终止验证过程并向所述数据处理服务器返回指示“验证成功”的验证结果，如果该时间差超过预定的阈值，则进入步骤（5）；（5）获取与该用户相关联的社交网站账户数据并抽取出该用户的所述特征属性，随之通过该用户识别模型计算该账户被分类为“正常账号”的概率值，随之将该概率值与预定的阈值（其由验证服务器的管理员配置）相比较并计算该账户的注册时间与当前时间的时间差，如果该概率值不超过所述预定的阈值并且所述时间差不超过预定的时间阈值（其由验证服务器的管理员配置），则在所述验证历史纪录数据库中纪录该账户的本次验证的验证时间、账户信息和验证结果并终止验证过程以及向所述数据处理服务器返回指示“验证成功”的验证结果，否则，终止验证过程以及向所述数据处理服务器返回指示“验证失败”的验证结果。Preferably, in the supplementary identity verification method disclosed in the present invention, the step (A3) further includes: (1) after receiving the supplementary verification request, the verification server prompts the user to log in to a specific social networking site (such as Weibo site, which has authorized the verification server to obtain relevant social networking site account data through the user's login operation) to obtain the social networking site account data associated with the user (which is provided by social networking website server to the verification server), wherein the user logs in to the social networking site using a second user identifier (that is, the user's social networking site account); (2) if the login operation fails, the verification server prompts the user "Login failed, unable to verify" and return the verification result indicating "unable to verify" to the data processing server, if the login operation is successful, enter step (3); (3) determine the current login by querying the verification history database Whether it is the first login of the user, and if it is the first login, associate the first user identifier with the second user identifier and record the association relationship in the verification history record database and enter the step ( 5) If it is not the first login, determine whether the second user identifier is associated with the verification record previously associated with the first user identifier by querying the verification history record database (that is, the previously recorded The association identifiers indicated in the association relationship related to a user identifier) are consistent. If they are not consistent, the verification process will be terminated and a verification result indicating "verification failure" will be returned to the data processing server. If they are consistent, go to step (4 ); (4) determine the time difference between the last successful verification time related to the second user identifier and the current time, if the time difference does not exceed a predetermined threshold, terminate the verification process and return an indication to the data processing server If the verification result of "verification is successful", if the time difference exceeds the predetermined threshold, go to step (5); (5) obtain the social networking site account data associated with the user and extract the user's characteristic attributes, and then The probability value of the account being classified as a "normal account" is calculated by the user identification model, and then the probability value is compared with a predetermined threshold (which is configured by the administrator of the verification server) and the registration time of the account and the current The time difference of time, if the probability value does not exceed the predetermined threshold and the time difference does not exceed the predetermined time threshold (which is configured by the administrator of the verification server), record the account's account in the verification history database The verification time, account information and verification result of the second verification and terminate the verification process and return the verification result indicating "verification successful" to the data processing server, otherwise, terminate the verification process and return the indication "verification failure" to the data processing server verification results.
优选地，在本发明所公开的辅助身份验证方法中，所述步骤（A3）进一步包括：如果验证失败的原因是注册时间与当前时间的时间差小于所述时间阈值，则提示用户“账号注册时间太短”。Preferably, in the auxiliary identity verification method disclosed in the present invention, the step (A3) further includes: if the reason for the verification failure is that the time difference between the registration time and the current time is less than the time threshold, prompting the user "account registration time too short".
由上可见，本发明所公开的辅助身份验证方法具有下列优点：具有广泛的适用性、并且便捷有效且成本较低。It can be seen from the above that the auxiliary identity verification method disclosed in the present invention has the following advantages: it has wide applicability, is convenient and effective, and has low cost.
尽管本发明是通过上述的优选实施方式进行描述的，但是其实现形式并不局限于上述的实施方式。应该认识到：在不脱离本发明主旨和范围的情况下，本领域技术人员可以对本发明做出不同的变化和修改。Although the present invention has been described through the above-mentioned preferred embodiments, its implementation forms are not limited to the above-mentioned embodiments. It should be appreciated that those skilled in the art can make various changes and modifications to the present invention without departing from the spirit and scope of the present invention.
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| CN201410837692.5ACN105591747B (en) | 2014-12-30 | 2014-12-30 | Auxiliary authentication method based on user network behavior characteristics |
| PCT/CN2015/097581WO2016107415A1 (en) | 2014-12-30 | 2015-12-16 | Auxiliary identity authentication method based on user network behavior feature |
| TW104143155ATW201633197A (en) | 2014-12-30 | 2015-12-22 | Auxiliary identity authentication method based on user network behavior feature |
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| CN201410837692.5ACN105591747B (en) | 2014-12-30 | 2014-12-30 | Auxiliary authentication method based on user network behavior characteristics |
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| CN105591747Atrue CN105591747A (en) | 2016-05-18 |
| CN105591747B CN105591747B (en) | 2019-11-22 |
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| CN201410837692.5AActiveCN105591747B (en) | 2014-12-30 | 2014-12-30 | Auxiliary authentication method based on user network behavior characteristics |
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