The method comprises the following steps that Yi represents the credit degree of a user i corresponding to a participating node device i, M represents the credibility of the participating node device i, and N represents the malicious degree of the participating node device i; mi represents the number of trusted messages sent by the participating node device i, and Ni represents the number of malicious/false messages sent by the participating node device i. M ═ Mi +1, N ═ Ni +1, and the initial values of Mi and Ni are 1. For the participating node device newly joining the live broadcast blockchain network, since the number of times of sending malicious/false messages in the live broadcast blockchain network is 0, the initial credit of the participating node device can be calculated to be 5 according to the formula (1). When the number of times of sending the trusted message sent by the participating node device increases, the credit degree of the participating node device becomes higher; as the number of malicious or false messages sent by a participating node device increases, the credit rating of the participating node device may become lower.

When a participating node device sends a message to the live blockchain network, the message may be an interaction message between the participating node devices, or may be an authentication message sent by the participating node devices to the live device 410.

When the live broadcast device 410 acquires a broadcast message sent by a certain participating node device (e.g., a first participating node device 420) from a live broadcast blockchain network, first, the signature of the broadcast message is verified, and whether the broadcast message is valid is determined (e.g., whether the broadcast message is complete and valid is determined by using an elliptic curve signature algorithm, and if the broadcast message is invalid, Ni of the first participating node device 420 is added by 1); and when the broadcast message is determined to be a valid message, obtaining a message type through analysis, wherein the message type represents whether the communication information carried in the broadcast message is interactive information or authentication information.

Upon determining that the information type is interaction information between the node to be confirmed and other participating nodes (e.g., interaction information between the first participating node device 420 and the second participating node device 430), the identifying means 411 of the malicious node in the live device 410 calculates a composite error of the interaction information; when the aggregate error is within an allowable range of the preset error threshold (e.g., the aggregate error is less than or equal to the preset error threshold), the trustworthiness M of the first participating node device 420 is determined to be Mi +1, otherwise, when the aggregate error is greater than the preset error threshold, the maliciousness N of the first participating node device 420 is determined to be Ni + 1.

When the information type is determined to be the authentication message sent by the first participating node device 420 to the live broadcast device 410, counting the number of trusted authentication identifiers and the number of malicious authentication identifiers in the authentication message obtained within a preset time length; when the number of trusted authentication identities is greater than half of the total number of participating nodes participating in the live broadcast service (e.g., the total number of participating nodes participating in the live broadcast service is 30, then when the number of trusted authentication identities is greater than 15), determining that the trustworthiness M of the first participating node device 420 is Mi + 1; otherwise, the degree of maliciousness N of the first participating node device 420 is determined to be Ni + 1.

From the above statistics of the various situations, and the calculations using equation (1), the latest credits for the various participating node devices (e.g., first participating node device 420) may be obtained. Then, the identifying means 411 of the malicious node in the live device 410 may obtain the user credit list according to the latest credit of each participating node device. When a certain latest credit in the user credit list is lower than a preset credit threshold (for example, the preset credit threshold is 5), it indicates that the participating node device corresponding to the latest information is a malicious node, and the identifying device 411 of the malicious node needs to write the identifier of the malicious node into the member certificate revocation list, and update the member authentication key of the malicious node (for example, replace the member authentication key of the malicious node with an invalid key), so that each node in the block link network knows that the malicious node has been prohibited from participating in the live broadcast service.

In this embodiment, a communication message and an information type sent by a node to be confirmed participating in a live broadcast service are acquired from a live broadcast blockchain network, where the information type is a type of information carried in the communication message; determining the credit degree of the node to be confirmed according to the communication message and the information type; according to the credit degree of the node to be confirmed and the user credit degree list, whether the node to be confirmed is a malicious node or not is determined, whether each participating node participating in the live broadcast service is a malicious user or not can be effectively identified, the malicious user is prevented from sending false information to a live broadcast block link network, the efficiency of the live broadcast service is improved, an operator can obtain real user demand information, the user can be better served, and the development of the live broadcast service is facilitated.

As shown in fig. 5, the electronic device 500 includes an input device 501, an input interface 502, a central processor 503, a memory 504, an output interface 505, an output device 506, and a bus 507. The input interface 502, the central processing unit 503, the memory 504, and the output interface 505 are connected to each other through a bus 507, and the input device 501 and the output device 506 are connected to the bus 507 through the input interface 502 and the output interface 505, respectively, and further connected to other components of the electronic device 500.

Specifically, the input device 501 receives input information from the outside and transmits the input information to the central processor 503 through the input interface 502; the central processor 503 processes input information based on computer-executable instructions stored in the memory 504 to generate output information, temporarily or permanently stores the output information in the memory 504, and then transmits the output information to the output device 506 through the output interface 505; the output device 506 outputs the output information to the outside of the electronic device 500 for use by the user.

In one embodiment, the electronic device shown in fig. 5 may be implemented as a system for identifying a malicious node, and the system for identifying a malicious node may include: a memory configured to store a program; a processor configured to execute the program stored in the memory to perform the method for identifying a malicious node described in the above embodiments.

The above are merely exemplary embodiments of the present application and are not intended to limit the scope of the present application. In general, the various embodiments of the application may be implemented in hardware or special purpose circuits, software, logic or any combination thereof. For example, some aspects may be implemented in hardware, while other aspects may be implemented in firmware or software which may be executed by a controller, microprocessor or other computing device, although the application is not limited thereto.

Embodiments of the application may be implemented by a data processor of a mobile device executing computer program instructions, for example in a processor entity, or by hardware, or by a combination of software and hardware. The computer program instructions may be assembly instructions, Instruction Set Architecture (ISA) instructions, machine related instructions, microcode, firmware instructions, state setting data, or source code or object code written in any combination of one or more programming languages.

Any logic flow block diagrams in the figures of this application may represent program steps, or may represent interconnected logic circuits, modules, and functions, or may represent a combination of program steps and logic circuits, modules, and functions. The computer program may be stored on a memory. The memory may be of any type suitable to the local technical environment and may be implemented using any suitable data storage technology, such as, but not limited to, Read Only Memory (ROM), Random Access Memory (RAM), optical storage devices and systems (digital versatile disks, DVDs, or CD discs), etc. The computer readable medium may include a non-transitory storage medium. The data processor may be of any type suitable to the local technical environment, such as but not limited to general purpose computers, special purpose computers, microprocessors, Digital Signal Processors (DSPs), Application Specific Integrated Circuits (ASICs), programmable logic devices (FGPAs), and processors based on a multi-core processor architecture.

It is to be understood that the above embodiments are merely exemplary embodiments that are employed to illustrate the principles of the present application, and that the present application is not limited thereto. It will be apparent to those skilled in the art that various changes and modifications can be made therein without departing from the spirit and scope of the application, and these changes and modifications are to be considered as the scope of the application.

Claims

1. A method for identifying a malicious node, the method comprising:

acquiring a first broadcast message sent by a node to be confirmed from a block chain network, wherein the node to be confirmed is a participating node participating in a live broadcast service, the first broadcast message comprises a communication message and an information type, and the information type is the type of information carried in the communication message;

determining the credit degree of the node to be confirmed according to the communication message and the information type;

and determining whether the node to be confirmed is a malicious node or not according to the credit rating of the node to be confirmed and a user credit rating list, wherein the user credit rating list comprises the credit rating of the participating node.

2. The method of claim 1, wherein the determining the credit of the node to be confirmed according to the communication message and the information type comprises:

judging whether the communication message is effective or not according to an elliptic curve signature algorithm;

when the communication message is determined to be valid, determining the credibility and the malicious degree of the node to be confirmed according to the information type; or, when the communication message is determined to be invalid, adding one to the malicious degree of the node to be confirmed, and keeping the credibility unchanged;

and calculating and obtaining the credit degree of the node to be confirmed according to the credibility and the malicious degree.

3. The method of claim 2, wherein said determining the trustworthiness and the maliciousness of the node to be validated according to the information type comprises:

when the information type is determined to be the interactive information between the node to be confirmed and other participating nodes, calculating the comprehensive error of the interactive information;

determining the credibility and the malicious degree of the node to be confirmed according to the comprehensive error and a preset error threshold;

when the information type is determined to be the authentication information, counting the number of credible authentication identifications and malicious authentication identifications in the authentication information obtained within a preset time length;

and determining the credibility and the maliciousness of the node to be confirmed according to the number of the credible authentication identifications, the maliciousness authentication identifications and the number of the participating nodes participating in the live broadcast service.

4. The method of claim 3, wherein the determining the trustworthiness and the maliciousness of the node to be confirmed according to the number of trusted authentication identifiers, the number of malicious authentication identifiers, and the number of participating nodes participating in the live broadcast service comprises:

calculating the credibility of the node to be confirmed according to the number of the credible authentication identifications and the number of the participating nodes participating in the live broadcast service;

and calculating and obtaining the malicious degree of the node to be confirmed according to the number of the malicious authentication identifications and the number of the participating nodes participating in the live broadcast service.

5. The method of claim 1, wherein the determining whether the node to be confirmed is a malicious node according to the credit of the node to be confirmed and a user credit list comprises:

determining a credit degree preset threshold value according to the credit degrees of all the participating nodes in the user credit degree list;

and determining whether the node to be confirmed is a malicious node or not according to the credit degree of the node to be confirmed and the preset threshold value of the credit degree.

6. The method according to claim 1, wherein after the step of determining whether the node to be confirmed is a malicious node according to the credit of the node to be confirmed and the user credit list, further comprising:

when the node to be confirmed is determined to be the malicious node, writing the identifier of the node to be confirmed into a member certificate revocation list;

and sending the member certificate revocation list to the block chain network so that the node to be confirmed can not participate in the live broadcast service.

7. The method of claim 6, wherein after the step of sending the member certificate revocation list to the blockchain network to disable the node to be confirmed from participating in the live traffic, further comprising:

and according to the member certificate revocation list, forbidding each participating node in the member certificate revocation list to participate in the live broadcast service.

8. The method of claim 7, wherein the prohibiting each participating node in the member certificate revocation list from participating in the live service in accordance with the member certificate revocation list comprises:

and updating member authentication keys of all the participating nodes in the member certificate revocation list according to the member certificate revocation list so that all the participating nodes in the member certificate revocation list cannot participate in the live broadcast service.

9. An apparatus for identifying a malicious node, comprising:

an obtaining module, configured to obtain, from a blockchain network, a first broadcast message sent by a node to be confirmed, where the node to be confirmed is a participating node participating in a live broadcast service, the first broadcast message includes a communication message and an information type, and the information type is a type of information carried in the communication message;

the credit degree determining module is used for determining the credit degree of the node to be confirmed according to the communication message and the information type;

and the identification module is used for determining whether the node to be confirmed is a malicious node or not according to the credit degree of the node to be confirmed and a user credit degree list, wherein the user credit degree list comprises the credit degree of the participating node.

10. An electronic device, comprising:

one or more processors;

memory having one or more programs stored thereon, which when executed by the one or more processors, cause the one or more processors to implement the method of identifying a malicious node as recited in any of claims 1-8.