A 5G message transmission method and system based on privacy protection

Abstract

The present application provides a 5G message transmission method and system based on privacy protection, which relates to the field of communication technology. Among them, the method includes: encrypting the content of the 5G message to be sent to generate an encrypted message; dividing the encrypted message into multiple encrypted message fragments, generating corresponding obfuscation information for each encrypted message fragment, and encrypting sensitive metadata to form a first data packet; generating a second data packet containing anonymous verification information based on the first data packet; using a multi-path selection algorithm, combined with a routing selection strategy to determine multiple transmission paths, and using a distributed hash table to assign tasks to each transmission path to obtain an assignment result; according to the assignment result, all second data packets are dispersedly transmitted so that the message receiving device reorganizes and decrypts all second data packets to restore the 5G message content. The technical solution provided by the present application enhances privacy protection and ensures the security and reliability of 5G message transmission.

Description

Technical Field

[0001] Embodiments of the present application relate to the field of communication technology, and in particular, to a 5G message transmission method and system based on privacy protection. Background Art

[0002] 5G message transmission is an important application in the fifth generation mobile communication technology (5G), which aims to provide efficient, secure and reliable message delivery services. With the popularization of 5G networks, users have higher requirements for the security and privacy protection of message transmission. Specific technical requirements include: high security, low latency, privacy protection and high reliability.

[0003] Existing 5G message transmission methods usually use the following steps to achieve secure message transmission: encrypt the content of the message to be sent, generate an encrypted message, and path transmit the encrypted message so that the message receiving device can decrypt the encrypted message to obtain the original 5G message.

[0004] However, the existing technology has weak anti-attack capabilities and is easy to be forged or tampered with. Once the data in the 5G message is tampered with, the integrity and reliability of the entire 5G message will be affected, and there is a problem of low reliability. Summary of the invention

[0005] The embodiments of the present application provide a 5G message transmission method and system based on privacy protection, so as to solve the problems of poor security and low reliability of 5G message transmission in the prior art.

[0006] In a first aspect, an embodiment of the present application provides a 5G message transmission method based on privacy protection, including:

[0007] Encrypt the content of the 5G message to be sent to generate an encrypted message;

[0008] The encrypted message is divided into a plurality of encrypted message segments, corresponding obfuscation information is generated for each encrypted message segment by a pseudo-random number generator, and the sensitive metadata is encrypted by applying homomorphic encryption technology to form a first data packet including the encrypted message segments, the obfuscation information and the encrypted sensitive metadata; the number of the first data packet is the same as the number of the encrypted message segments;

[0009] In combination with the zero-knowledge proof result corresponding to each first data packet, a group of ring members are selected from the target candidate pool by applying the ring member selection optimization algorithm, anonymous verification information corresponding to each first data packet is determined in combination with the group of ring members, and a second data packet containing the anonymous verification information is generated; all second data packets together constitute a set of data packets to be transmitted; the anonymity contribution value of the candidate members in the target candidate pool is greater than or equal to a preset contribution threshold, and the anonymity contribution value is calculated according to the activity level and association strength of the candidate members;

[0010] Using a multi-path selection algorithm and combining it with a routing selection strategy to determine multiple transmission paths, and based on the set of data packets to be transmitted, using a distributed hash table to perform task allocation for each transmission path to obtain an allocation result;

[0011] The set of data packets to be transmitted are transmitted in a dispersed manner according to the allocation result, so that after the message receiving device receives all the second data packets, based on the security keys pre-exchanged and negotiated through the multi-party computing protocol, all the second data packets are reorganized and decrypted using a threshold decryption scheme to remove obfuscated information and restore the 5G message content.

[0012] Optionally, combining the zero-knowledge proof result corresponding to each first data packet, applying a ring member selection optimization algorithm to select a group of ring members from a target candidate pool, combining the group of ring members to determine the anonymous verification information corresponding to each first data packet, and generating a second data packet containing the anonymous verification information, includes:

[0013] Using a zero-knowledge proof mechanism, according to predefined protocol rules, a corresponding zero-knowledge proof result is generated for each of the first data packets;

[0014] Based on the zero-knowledge proof result, a ring member selection optimization algorithm is applied to select a group of ring members from a target candidate pool to form a ring member combination, wherein the ring member combination includes an actual message sending device and a non-actual message sending device;

[0015] Based on the private key of the actual message sending device and the public key of the non-actual message sending device, an anonymous verification message is generated using the ring signature algorithm;

[0016] The anonymous verification message is added to the first data packet to form a second data packet.

[0017] Optionally, the selecting a group of ring members from a target candidate pool by applying a ring member selection optimization algorithm based on the zero-knowledge proof result includes:

[0018] According to the system registration information and the device communication history records, an initial candidate pool including all potential message sending devices is established, and potential message sending devices known to be offline or unable to participate in signing are removed from the initial candidate pool to obtain an intermediate candidate pool; the initial candidate pool includes actual message sending devices, and the actual message sending devices are identified to be retained in the intermediate candidate pool;

[0019] Determine the activity level of each candidate member in the intermediate candidate pool and the strength of association between the candidate member and the actual message sending device according to the zero-knowledge proof result, and calculate the anonymity contribution value of each candidate member in the intermediate candidate pool according to the activity level and the strength of association;

[0020] Screening candidate members whose anonymity contribution value is greater than or equal to a preset contribution threshold to form a target candidate pool;

[0021] The number of ring members is determined according to predefined security parameters, and a group of ring members is selected from the target candidate pool by applying a ring member selection optimization algorithm according to the number of ring members to form a ring member combination.

[0022] Optionally, calculating the anonymity contribution value of each candidate member in the intermediate candidate pool according to the activity level and the association strength includes:

[0023] For each candidate member in the intermediate candidate pool, the activity level of the candidate member is quantified based on the number of active days, average online time and number of communications, and a historical activity frequency value is obtained;

[0024] Constructing hidden Markov models corresponding to the number of times of jointly participating in communication, the strength of social relationship and the proximity of geographical location respectively, using the corresponding hidden Markov models to respectively calculate the pattern similarity, social relationship strength and geographical location proximity of the candidate members and the actual message sending device jointly participating in communication, and weightedly summing the pattern similarity, social relationship strength and geographical location proximity of the candidate members and the actual message sending device jointly participating in communication to quantify the association strength of the candidate members to obtain an association value;

[0025] The weighted sum of the historical activity frequency value and the association value is determined as the anonymity contribution value of the candidate member.

[0026] Optionally, the ring member selection optimization algorithm may include a genetic algorithm, and the step of applying the ring member selection optimization algorithm to select a group of ring members from the target candidate pool according to the number of ring members includes:

[0027] Generate an initial population according to the number N of the ring members, each individual in the initial population represents a ring member combination, and the ring member combination includes 1 actual message sending device and N-1 non-actual message sending devices;

[0028] The fitness function is defined based on the sum of the anonymity contribution values ​​of all ring members, the quantitative results of the diversity of the ring member combination, and the probability of the ring member combination being successfully attacked. The fitness function uses the following formula:

[0029] ;

[0030] in, is the fitness value of the ring member combination, Is the first member of the ring The anonymity contribution value of each ring member; It represents the sum of the anonymity contribution values ​​of all ring members in the ring member combination, and N represents the number of ring members; It is the quantitative result of the diversity of the ring member combinations; is the probability that a combination of ring members is successfully attacked; is the weight coefficient of the corresponding item, which is used to balance the influence of different factors;

[0031] The individuals in the population are sorted according to the fitness function, and selection operations, crossover operations and mutation operations are performed to obtain the next generation population; the population is the initial population when the number of iterations is 1, and is the next generation population when the number of iterations is other values ​​greater than 1;

[0032] Determine whether the preset stop iteration condition is reached. If not, repeat the sorting, selection, crossover and mutation operations, as well as the judgment operation, until the preset stop iteration condition is reached. The preset stop iteration condition is that the maximum number of iterations is reached, or the fitness function value of the best individual in the last generation of the population is greater than or equal to the preset function threshold, or the fitness change degree of the population is less than the preset change threshold.

[0033] Optionally, the process of obtaining the probability of a ring member combination being successfully attacked includes:

[0034] For simulated attack scenarios of multiple attack types, corresponding attack parameters, attack tools, tool techniques and attack targets are set to build a simulated attack model; the multiple attack types include traffic analysis attacks, behavior pattern attacks, replay attacks, man-in-the-middle attacks and social engineering attacks; the attack parameters include: attack intensity, attack frequency and attack duration; the attack target is at least one of an actual message sending device and a non-actual message sending device;

[0035] Calculating the success probability of each attack type using the simulated attack model;

[0036] The success probabilities of all attack types are weighted and summed to obtain the total probability of a ring member combination being successfully attacked.

[0037] Optionally, the step of generating an anonymous verification message using a ring signature algorithm based on a private key of an actual message sending device and a public key of a non-actual message sending device includes:

[0038] Obtain the private key of the actual message sending device and the public key of the non-actual message sending device;

[0039] The public key of the non-actual message sending device is hashed in combination with the timestamp to obtain a corresponding hash value; if there are multiple non-actual message sending devices, all hash values ​​are linked to obtain a chain hash structure;

[0040] Based on the private key of the actual message sending device and the chain hash structure, an anonymous verification message is generated using a ring signature algorithm.

[0041] In a second aspect, an embodiment of the present application provides a 5G message transmission system based on privacy protection, including:

[0042] An encryption module is used to encrypt the content of the 5G message to be sent and generate an encrypted message;

[0043] a segmentation generation module, configured to segment the encrypted message into a plurality of encrypted message segments, generate corresponding obfuscation information for each encrypted message segment by a pseudo-random number generator, and encrypt the sensitive metadata by applying homomorphic encryption technology to form a first data packet including the encrypted message segments, the obfuscation information and the encrypted sensitive metadata; the number of the first data packets is the same as the number of the encrypted message segments;

[0044] A determination module, used to select a group of ring members from a target candidate pool by applying a ring member selection optimization algorithm in combination with a zero-knowledge proof result corresponding to each first data packet, determine the anonymous verification information corresponding to each first data packet in combination with the group of ring members, and generate a second data packet containing the anonymous verification information; all second data packets together constitute a set of data packets to be transmitted; an anonymity contribution value of a candidate member in the target candidate pool is greater than or equal to a preset contribution threshold, and the anonymity contribution value is calculated based on the activity level and association strength of the candidate member;

[0045] An allocation module is used to determine multiple transmission paths by using a multi-path selection algorithm in combination with a routing selection strategy, and based on the set of data packets to be transmitted, use a distributed hash table to perform task allocation for each transmission path to obtain an allocation result;

[0046] The transmission module is used to disperse the set of data packets to be transmitted according to the allocation result, so that after the message receiving device receives all the second data packets, it uses a threshold decryption scheme to reorganize and decrypt all the second data packets based on the security keys pre-exchanged and negotiated through the multi-party computing protocol to remove obfuscated information and restore the 5G message content.

[0047] In a third aspect, an embodiment of the present application provides a computing device, comprising a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a privacy protection-based 5G message transmission method as described in any one of the first aspects.

[0048] In a fourth aspect, an embodiment of the present application provides a computer storage medium storing a computer program. When the computer program is executed by a computer, it implements a 5G message transmission method based on privacy protection as described in any one of the first aspects.

[0049] In an embodiment of the present application, a 5G message transmission method based on privacy protection is provided, including: encrypting the content of a 5G message to be sent to generate an encrypted message; dividing the encrypted message into multiple encrypted message segments, generating corresponding obfuscation information for each encrypted message segment through a pseudo-random number generator, and applying homomorphic encryption technology to encrypt sensitive metadata to form a first data packet including the encrypted message segments, the obfuscation information and the encrypted sensitive metadata; the number of the first data packets is the same as the number of the encrypted message segments; combining the zero-knowledge proof result corresponding to each first data packet, applying a ring member selection optimization algorithm to select a group of ring members from a target candidate pool, combining the group of ring members to determine the anonymous verification information corresponding to each first data packet, and generating a second data packet containing the anonymous verification information data packets; all second data packets together constitute a data packet set to be transmitted; the anonymity contribution value of the candidate members in the target candidate pool is greater than or equal to a preset contribution threshold, and the anonymity contribution value is calculated according to the activity level and association strength of the candidate members; a multi-path selection algorithm is used in combination with a routing selection strategy to determine multiple transmission paths, and based on the data packet set to be transmitted, a distributed hash table is used to perform task allocation for each transmission path to obtain an allocation result; according to the allocation result, the data packet set to be transmitted is dispersedly transmitted, so that after the message receiving device receives all the second data packets, based on the security keys pre-exchanged and negotiated through the multi-party computing protocol, a threshold decryption scheme is used to reorganize and decrypt all the second data packets to remove obfuscated information and restore the 5G message content.

[0050] This embodiment generates corresponding anonymous verification information for each first data packet, thereby ensuring that each second data packet will not leak the identity information of the actual message sending device during transmission, enhancing the privacy protection capability, making it difficult for an attacker to associate with the actual message sending device even if he intercepts part of the second data packet, thereby improving the security and reliability of 5G message transmission. In the specific implementation process, the anonymity contribution value of the candidate members selected from the target candidate pool in this embodiment is greater than or equal to the preset contribution threshold, and the anonymity contribution value is calculated based on the activity level and association strength of the candidate members, so that it can be ensured that each ring member helps to increase anonymity, improves the overall anonymity of the ring member combination, and makes it difficult for an attacker to determine the actual sender; by applying the ring member selection optimization algorithm, it is ensured that the selected ring member combination not only meets the requirements of the security parameters, but also has the highest anonymity and reliability. At the same time, this embodiment provides a multi-layer encryption mechanism, combined with obfuscated information and homomorphic encryption technology, to further improve the security of the data. Even if the attacker can obtain the encrypted message fragments and sensitive metadata, it is impossible to directly decrypt or use this information. Anonymous verification information is not only used to verify the authenticity of the data packet, but also to detect whether the data has been tampered with. By using a multi-path selection algorithm combined with a routing selection strategy, it is ensured that the set of data packets to be transmitted can be dispersedly transmitted on multiple transmission paths, which can not only avoid congestion on a single route, but also improve the overall transmission efficiency. The task allocation mechanism based on a distributed hash table can effectively distribute transmission tasks to different paths, make full use of network resources, and reduce transmission delays and packet loss rates. Since the second data packet is transmitted in a dispersed manner and reassembled and decrypted at the receiving end, even if the attacker can intercept part of the second data packet, it is difficult to obtain the complete message content from it. This mechanism improves the system's anti-attack capability. This embodiment introduces a zero-knowledge proof mechanism, a ring signature algorithm, and a complex anonymity contribution value calculation process, which can further enhance privacy protection capabilities.

[0051] These and other aspects of the present application will become more clearly understood in the description of the following embodiments. BRIEF DESCRIPTION OF THE DRAWINGS

[0052] In order to more clearly illustrate the embodiments of the present application or the technical solutions in the prior art, a brief introduction will be given below to the drawings required for use in the embodiments or the description of the prior art. Obviously, the drawings described below are some embodiments of the present application. For ordinary technicians in this field, other drawings can be obtained based on these drawings without paying any creative work.

[0053] Figure 1 A flowchart of a 5G message transmission method based on privacy protection provided in an embodiment of the present application;

[0054] Figure 2A schematic diagram of the structure of a 5G message transmission system based on privacy protection provided in an embodiment of the present application;

[0055] Figure 3 A schematic diagram of the structure of a computing device provided in an embodiment of the present application. DETAILED DESCRIPTION

[0056] In order to enable those skilled in the art to better understand the solution of the present application, the technical solution in the embodiments of the present application will be clearly and completely described below in conjunction with the drawings in the embodiments of the present application.

[0057] In some of the processes described in the specification and claims of this application and the above-mentioned figures, multiple operations that appear in a specific order are included, but it should be clearly understood that these operations may not be executed in the order in which they appear in this article or executed in parallel. The sequence numbers of the operations, such as 11, 12, etc., are only used to distinguish between different operations, and the sequence numbers themselves do not represent any execution order. In addition, these processes may include more or fewer operations, and these operations may be executed in sequence or in parallel. It should be noted that the descriptions of "first", "second", etc. in this article are used to distinguish different messages, devices, modules, etc., do not represent the order of precedence, and do not limit the "first" and "second" to different types.

[0058] The following will be combined with the drawings in the embodiments of the present application to clearly and completely describe the technical solutions in the embodiments of the present application. Obviously, the described embodiments are only part of the embodiments of the present application, not all of the embodiments. Based on the embodiments in the present application, all other embodiments obtained by those skilled in the art without creative work are within the scope of protection of this application.

[0059] Figure 1 A flowchart of a 5G message transmission method based on privacy protection provided in an embodiment of the present application is as follows: Figure 1 As shown, the method includes:

[0060] S11. Encrypt the content of the 5G message to be sent to generate an encrypted message.

[0061] Among them, 5G message content can be text or multimedia content (such as pictures, videos, etc.).

[0062] Optionally, this embodiment can use the quantum key distribution protocol, combined with symmetric and asymmetric key technology and forward security signature mechanism, to encrypt the 5G message content, ensuring that only authorized message receiving devices can decrypt and read the 5G message content, to prevent unauthorized third parties from obtaining or tampering with the 5G message content. For example, a 5G message containing a user chat record will be encrypted before sending to ensure that the user chat record will not be eavesdropped or tampered with during transmission.

[0063] S12, dividing the encrypted message into a plurality of encrypted message segments, generating corresponding obfuscation information for each encrypted message segment by a pseudo-random number generator, and applying homomorphic encryption technology to encrypt the sensitive metadata to form a first data packet including the encrypted message segments, the obfuscation information, and the encrypted sensitive metadata. The number of the first data packets is the same as the number of the encrypted message segments.

[0064] This embodiment does not specifically limit the number of encrypted message fragments, and different encrypted message fragments can be of the same length or of different lengths, which is not specifically limited in this embodiment. The pseudo-random number generator is used to generate a seemingly random but repeatable digital sequence, generate obfuscation information for each encrypted message fragment, and increase security during transmission. Accordingly, obfuscation information is random data attached to each encrypted message fragment, which is used to obfuscate the message content, making it difficult for attackers to analyze and crack it. Homomorphic encryption technology is a technology that allows calculations to be performed directly on encrypted data without decryption, and is suitable for protecting sensitive metadata (such as timestamps, source addresses, etc.) to ensure that these data are not leaked during transmission. For example, a long message is divided into multiple small fragments. After the metadata is homomorphically encrypted, each fragment and the corresponding obfuscation information and metadata are encapsulated into a first data packet, ready for further processing and transmission.

[0065] S13. In combination with the zero-knowledge proof result corresponding to each first data packet, a group of ring members are selected from the target candidate pool using a ring member selection optimization algorithm, anonymous verification information corresponding to each first data packet is determined in combination with the group of ring members, and a second data packet containing the anonymous verification information is generated; all second data packets together constitute a set of data packets to be transmitted, and the anonymity contribution value of the candidate members in the target candidate pool is greater than or equal to a preset contribution threshold, and the anonymity contribution value is calculated based on the activity level and association strength of the candidate members.

[0066] The anonymous verification information is used to verify the authenticity and integrity of each first data packet, while ensuring that the identity information of the actual message sending device is not leaked. Exemplarily, the anonymous verification information can be generated using a zero-knowledge proof mechanism and a ring signature algorithm. The second data packet is an extended data unit consisting of the first data packet and the anonymous verification information, and is used for actual transmission.

[0067] S14. Determine multiple transmission paths by using a multi-path selection algorithm in combination with a routing selection strategy, and use a distributed hash table to assign tasks to each transmission path based on a set of data packets to be transmitted to obtain an assignment result.

[0068] Among them, the multi-path selection algorithm is used to select multiple different transmission paths to avoid congestion or failure problems that may occur on a single path, and improve transmission efficiency and reliability. The routing selection strategy can select the optimal transmission path based on factors such as network status and load conditions. The distributed hash table is a distributed key-value storage system used to efficiently allocate and manage transmission tasks. Task allocation refers to allocating each data packet in a data packet set to different transmission paths to ensure the effective use of resources.

[0069] For example, this embodiment selects several low-latency, high-bandwidth paths according to the current network conditions, and then uses a distributed hash table to allocate corresponding second data packets to each transmission path to ensure that the workload of each path is balanced. Finally, a detailed allocation result is obtained.

[0070] S15. The set of data packets to be transmitted is transmitted in a dispersed manner according to the allocation result, so that after the message receiving device receives all the second data packets, based on the security keys pre-exchanged and negotiated through the multi-party computing protocol, all the second data packets are reassembled and decrypted using a threshold decryption scheme to remove obfuscated information and restore the 5G message content.

[0071] Among them, decentralized transmission can transmit each data packet in a data packet set through different paths, thereby improving transmission efficiency and anti-attack capabilities. The security key may refer to a security key pre-exchanged through a multi-party computing protocol to ensure that only legitimate message receiving devices can decrypt the second data packet. The threshold decryption scheme is a distributed decryption method that can only successfully decrypt when a certain number of second data packets are reached, increasing fault tolerance and security. For example, the message receiving device can only successfully decrypt and remove obfuscated information when it collects enough second data packets (such as more than half), and finally restore the original 5G message content. The decryption process ensures that even if some data packets are lost or intercepted, the complete message content can still be restored.

[0072] By executing steps S11 to S15, the embodiment of the present application combines anonymous verification information and decentralized transmission, enhances privacy protection and anti-attack capabilities, and ensures the confidentiality, integrity and availability of 5G messages during transmission. Specifically, by generating corresponding anonymous verification information for each first data packet, the embodiment ensures that each second data packet will not leak the identity information of the actual message sending device during transmission, enhances privacy protection capabilities, and makes it difficult for attackers to associate with the actual message sending device even if they intercept part of the second data packet, thereby improving the security and reliability of 5G message transmission. In the specific implementation process, the anonymity contribution values ​​of the candidate members selected from the target candidate pool in the embodiment are greater than or equal to the preset contribution threshold, and the anonymity contribution values ​​are calculated based on the activity level and association strength of the candidate members, so that each ring member can help increase anonymity, improve the overall anonymity of the ring member combination, and make it difficult for attackers to determine the actual sender; by applying the ring member selection optimization algorithm, it is ensured that the selected ring member combination not only meets the requirements of security parameters, but also has the highest anonymity and reliability. At the same time, the embodiment provides a multi-layer encryption mechanism, combined with obfuscated information and homomorphic encryption technology, to further improve the security of data. Even if an attacker can obtain encrypted message fragments and sensitive metadata, they cannot directly decrypt or use this information. Anonymous verification information is not only used to verify the authenticity of the data packet, but also to detect whether the data has been tampered with. The multi-path selection algorithm is combined with the routing selection strategy to ensure that the set of data packets to be transmitted can be distributed on multiple transmission paths, which can not only avoid congestion on a single route, but also improve the overall transmission efficiency. The task allocation mechanism based on the distributed hash table can effectively distribute the transmission tasks to different paths, make full use of network resources, and reduce transmission delays and packet loss rates. Since the second data packet is transmitted in a dispersed manner and reassembled and decrypted at the receiving end, even if the attacker can intercept part of the second data packet, it is difficult to obtain the complete message content from it. This mechanism improves the system's anti-attack capability.

[0073] In a possible embodiment, step S13, combining the zero-knowledge proof result corresponding to each first data packet, applying the ring member selection optimization algorithm to select a group of ring members from the target candidate pool, combining the group of ring members to determine the anonymous verification information corresponding to each first data packet, and generating a second data packet containing the anonymous verification information, includes:

[0074] Step 131: Utilize the zero-knowledge proof mechanism and generate a corresponding zero-knowledge proof result for each first data packet according to predefined protocol rules.

[0075] Among them, zero-knowledge proof is a cryptographic protocol. In 5G message transmission, zero-knowledge proof is used to generate anonymous verification information to ensure that the verification process does not leak any sensitive information. The predefined protocol rules include verification rules, encryption algorithms, and communication standards, etc., to ensure that all participating devices follow the same rules to generate and verify zero-knowledge proofs. The result of zero-knowledge proof is a data structure containing verification information, which is used to prove the validity and integrity of the first data packet without revealing its specific content or the identity information of the actual message sending device. The zero-knowledge proof mechanism not only protects the content of 5G messages, but also ensures the security and privacy of the verification process itself to prevent the leakage of any sensitive information.

[0076] Step 132: Based on the zero-knowledge proof result, a ring member selection optimization algorithm is applied to select a group of ring members from the target candidate pool to form a ring member combination, where the ring member combination includes actual message sending devices and non-actual message sending devices.

[0077] Among them, the ring member combination is an anonymous set consisting of an actual message sending device and several non-actual message sending devices. Each ring member helps to increase anonymity, making it difficult for attackers to determine the actual sender. The zero-knowledge proof result is used to evaluate the historical activity frequency value and correlation value of each device in the target candidate pool, thereby calculating its anonymity contribution value and finally selecting the optimal ring member combination. By introducing the ring member combination, the actual message sending device can be verified without exposing its identity, thereby enhancing anonymity.

[0078] As an optional implementation, step 132, based on the zero-knowledge proof result, applying a ring member selection optimization algorithm to select a group of ring members from the target candidate pool includes:

[0079] Step a1: establish an initial candidate pool containing all potential message sending devices based on system registration information and device communication history records, remove potential message sending devices that are known to be offline or unable to participate in signing from the initial candidate pool, and obtain an intermediate candidate pool; the initial candidate pool includes actual message sending devices, and the actual message sending devices are identified to be retained in the intermediate candidate pool.

[0080] Among them, the system registration information includes basic information such as the identification, type, and user of all registered message sending devices. These data are used to preliminarily screen potential message sending devices. Device communication history: used to record the historical communication behavior of each registered message sending device, such as active time, communication frequency, interaction with other devices, etc. These data are used to evaluate the activity and reliability of registered message sending devices. Devices that are offline or unable to participate in signing may refer to devices that are currently offline or unable to participate in the signing process due to other reasons (such as hardware failure, network problems, etc.). These devices need to be removed from the initial candidate pool. The actual message sending device is the device that actually initiates the message transmission and must remain in the candidate pool throughout the process and be clearly identified to ensure its participation in subsequent steps.

[0081] For example, there is an initial candidate pool containing 100 devices. By checking the device status (such as online status, battery level, etc.), 20 devices that are offline or unable to participate in signing are removed, and an intermediate candidate pool containing 80 devices is obtained. At the same time, ensure that the actual message sending device is always retained and identified in the intermediate candidate pool.

[0082] Step a2: Determine the activity level of each candidate member in the intermediate candidate pool and the strength of association between the candidate member and the actual message sending device based on the zero-knowledge proof result, and calculate the anonymity contribution value of each candidate member in the intermediate candidate pool based on the activity level and the strength of association. The strength of association is used to measure the strength of the relationship between the candidate member and the actual message sending device. Quantify the activity level and the strength of association respectively, and then calculate the anonymity contribution value of each candidate member in the intermediate candidate pool based on the quantification results.

[0083] Step a3: Screen candidate members whose anonymity contribution values ​​are greater than or equal to a preset contribution threshold to form a target candidate pool.

[0084] Among them, the preset contribution threshold is a minimum anonymity contribution value standard set according to security requirements to ensure that only candidate members who meet or exceed this standard can enter the target candidate pool. The target candidate pool is a set of candidate members with high anonymity contribution values ​​formed after screening, which is used for the selection of subsequent ring members. By setting a preset contribution threshold, it is ensured that only devices with high anonymity contribution values ​​enter the target candidate pool, thereby improving the overall anonymity of the ring member combination. This embodiment reduces the number of devices participating in the ring signature, reduces the risk of attack, and enhances the security of 5G message transmission.

[0085] Step a4: determine the number of ring members according to predefined security parameters, and select a group of ring members from the target candidate pool using a ring member selection optimization algorithm according to the number of ring members to form a ring member combination.

[0086] Among them, the safety parameter refers to a predefined safety parameter, which determines the number of ring members and is usually adjusted according to the needs of specific application scenarios. The ring member selection optimization algorithm is an optimization algorithm used to select the optimal ring member combination from the target candidate pool. It can include genetic algorithms, particle swarm optimization, etc.

[0087] Exemplarily, in 5G message transmission, assuming that the predefined security parameters determine that the number of ring members is 10, a genetic algorithm is applied to select a set of optimal ring member combinations from the target candidate pool. For example, through multiple iterations and optimizations, 10 devices are finally selected as the ring member combination, including the actual message sending device and 9 other devices with high anonymity contribution values. By applying the ring member selection optimization algorithm, it is ensured that the selected ring member combination not only meets the requirements of the security parameters, but also has the highest anonymity and reliability. According to different application scenarios and security requirements, the number and selection strategy of ring members are flexibly adjusted to improve the flexibility and adaptability of the embodiments of the present application.

[0088] By executing steps a1 to a4, the embodiment of the present application flexibly adjusts the number and selection strategy of ring members according to different application scenarios and security requirements, thereby improving the flexibility and adaptability of the embodiment of the present application.

[0089] Step 133: Based on the private key of the actual message sending device and the public key of the non-actual message sending device, an anonymous verification message is generated using a ring signature algorithm.

[0090] Among them, the ring signature algorithm is a digital signature scheme that allows the signer to hide his or her identity in an anonymous set while ensuring the validity of the signature. The ring signature algorithm enables the actual message sending device to be verified without exposing its identity, preventing identity tracking and leakage. Anonymous verification messages not only verify the authenticity and integrity of data packets, but also prevent forgery and tampering attacks, improving the security of 5G message transmission.

[0091] As a possible implementation, step 133, based on the private key of the actual message sending device and the public key of the non-actual message sending device, generates an anonymous verification message using a ring signature algorithm, including:

[0092] Step b1: Obtain the private key of the actual message sending device and the public key of the non-actual message sending device.

[0093] Among them, the private key is used to sign and generate anonymous verification messages to ensure the authenticity and integrity of the message. The public keys of all non-actual message sending devices can form a public key set to build a chain hash structure to enhance anonymity.

[0094] Exemplarily, the actual message sending device is mobile phone A, which holds the private key SKA. The non-actual message sending devices include mobile phones B, C and D, which hold public keys PKB, PKC and PKD respectively. In step b1, mobile phone A obtains its own private key SKA and the public keys PKB, PKC and PKD of mobile phones B, C and D. By clearly distinguishing the private key of the actual message sending device and the public key of the non-actual message sending device, the key management process is simplified and the risk of key leakage is reduced. In an embodiment of the present application, the actual message sending device holds the private key, which ensures the authenticity of the signature and enhances the security of the system.

[0095] Step b2: hash the public key of the non-actual message sending device in combination with the timestamp to obtain a corresponding hash value; if there are multiple non-actual message sending devices, link all hash values ​​to obtain a chain hash structure.

[0096] Among them, hash processing refers to the use of hash functions to process the public key and timestamp of each non-actual message sending device to generate a unique hash value. The hash value has a fixed length and it is difficult to reversely derive the original data. When there are multiple non-actual message sending devices, the hash values ​​are linked in sequence to form a chain structure. This structure not only increases the complexity, but also improves the anti-tampering ability. The introduction of timestamps can prevent replay attacks and ensure that each generated hash value is unique. The chain hash structure makes it difficult for attackers to track which specific device participated in the signature, thereby enhancing anonymity.

[0097] Step b3: Based on the private key of the actual message sending device and the chain hash structure, a ring signature algorithm is used to generate an anonymous verification message.

[0098] Optionally, this embodiment can also allocate a unique one-time verification token to the generation process of the anonymous verification message through a one-time verification token, thereby further improving the reliability of 5G message transmission.

[0099] Exemplarily, mobile phone A uses its own private key SKA and chain hash structure H to generate an anonymous verification message Sig through a ring signature algorithm. The anonymous verification message includes signature information and a chain hash structure, ensuring the authenticity and anonymity of the second data packet generated subsequently.

[0100] By executing steps b1 to b3, the embodiment of the present application simplifies the key management process and reduces the risk of key leakage by clearly distinguishing the private key of the actual message sending device and the public key of the non-actual message sending device. This embodiment introduces a timestamp to ensure that each generated hash value is unique, effectively preventing replay attacks. The chained hash structure increases the complexity of the signature, making it difficult for attackers to determine the specific signer, further enhancing anonymity. The ring signature algorithm ensures that even if an attacker intercepts the anonymous verification message, it is impossible to determine which specific device is the actual message sender.

[0101] Step 134: Add the anonymous verification message to the first data packet to form a second data packet.

[0102] The first data packet includes the encrypted message fragment, obfuscated information, and encrypted sensitive metadata. The second data packet adds an anonymous verification message to the first data packet to form a complete data packet to be transmitted. This embodiment does not specifically limit the format and location of different information.

[0103] By adding anonymous verification messages, the authenticity and integrity of each data packet is ensured, preventing the data packet from being tampered with or forged. The message receiving device can directly verify the second data packet using the security key that was pre-exchanged and negotiated through the multi-party computing protocol, simplifying the verification process and improving parsing efficiency.

[0104] By executing steps 131 to 134, the embodiment of the present application introduces a zero-knowledge proof mechanism and a ring signature algorithm to achieve a higher level of anonymity and privacy protection, and prevent identity leakage and tracking. A more complex verification mechanism is introduced to ensure the integrity and anti-tampering ability of the 5G message content. Through multi-dimensional evaluation and optimization algorithms, the optimal combination of ring members is accurately screened out, improving reliability and transmission efficiency. The use of multi-party computing protocols and distributed transmission mechanisms enhances anti-attack capabilities and robustness. In addition, this embodiment can dynamically adjust the number of ring members and optimize task allocation, improve the flexibility and adaptability of the method, and better cope with complex and changing network environments.

[0105] In the above embodiment, in step a2, the anonymity contribution value of each candidate member in the intermediate candidate pool is calculated according to the activity level and the association strength, including:

[0106] Step a21: for each candidate member in the intermediate candidate pool, the activity level of the candidate member is quantified based on the number of active days, average online time and number of communications to obtain a historical activity frequency value.

[0107] Step a22: construct hidden Markov models corresponding to the number of times of joint participation in communication, social relationship strength and geographical location proximity respectively, use the corresponding hidden Markov models to calculate the pattern similarity, social relationship strength and geographical location proximity of the candidate members' joint participation in communication with the actual message sending device respectively, and take the weighted sum of the pattern similarity, social relationship strength and geographical location proximity of the candidate members' joint participation in communication with the actual message sending device to quantify the association strength of the candidate members and obtain the association value.

[0108] Step a23: Determine the weighted sum of the historical activity frequency value and the association value as the anonymity contribution value of the candidate member.

[0109] By executing steps a21 to a23, the embodiment of the present application can comprehensively evaluate the anonymity contribution of each candidate member from multiple perspectives based on the historical activity frequency value (active days, average online time, number of communications) and the association value (number of co-participated communications, social relationship strength, and geographic proximity). The hidden Markov model is used to calculate the pattern similarity, social relationship strength, and geographic proximity respectively, capturing more complex behavior patterns and association relationships. This method not only improves the accuracy of the evaluation, but also enhances the flexibility and adaptability of the method. By calculating the pattern similarity of candidate members and actual message sending devices participating in the communication through the hidden Markov model, members with abnormal behavior patterns can be identified, thereby eliminating potential security threats, enhancing the anti-attack ability of the method, and preventing forgery and tampering attacks. Combined with the strength of social relationships and geographic proximity, it is ensured that the selected ring members have high anonymity and reliability. Even if the attacker has some information, it is difficult to infer the identity of the actual message sender by analyzing these factors. The historical activity frequency value and the association value are weighted and summed to determine the final anonymity contribution value. This mechanism can dynamically adjust the weight coefficient according to the specific application scenario, flexibly balance the influence of different factors, and ensure the selection of the optimal combination of ring members.

[0110] In the above embodiment, the ring member selection optimization algorithm exemplarily includes a genetic algorithm. Accordingly, in step a4, according to the number of ring members, a group of ring members are selected from the target candidate pool by applying the ring member selection optimization algorithm, including:

[0111] Step a41: Generate an initial population according to the number N of ring members, where each individual in the initial population represents a ring member combination, and the ring member combination includes 1 actual message sending device and N-1 non-actual message sending devices.

[0112] Step a42: Define a fitness function based on the sum of the anonymity contribution values ​​of all ring members, the diversity quantification result of the ring member combination, and the probability of the ring member combination being successfully attacked.

[0113] The fitness function can be expressed as follows:

[0114] ;

[0115] in, is the fitness value of the ring member combination, Is the first member of the ring The anonymity contribution value of each ring member; It represents the sum of the anonymity contribution values ​​of all ring members in the ring member combination, and N represents the number of ring members; It is the quantitative result of the diversity of the ring member combinations; is the probability that a combination of ring members is successfully attacked; It is the weight coefficient of the corresponding item, which is used to balance the influence of different factors.

[0116] The process of obtaining the probability of a ring member combination being successfully attacked includes:

[0117] Step a421, for simulated attack scenarios of multiple attack types, set corresponding attack parameters, attack tools, tool techniques and attack targets to build a simulated attack model; multiple attack types include traffic analysis attacks, behavior pattern attacks, replay attacks, man-in-the-middle attacks and social engineering attacks; attack parameters include: attack intensity, attack frequency and attack duration; the attack target is at least one of the actual message sending devices and non-actual message sending devices.

[0118] Among them, the traffic analysis attack can infer the identity of the actual message sending device by observing the communication traffic pattern, including analyzing the characteristics such as the size, frequency and time interval of the data packet. The behavior pattern attack is used to try to identify members with abnormal behavior or frequent participation in signing based on the historical activity frequency and behavior pattern of the ring members. Replay attack refers to the attacker intercepting and replaying the legitimate ring signature in an attempt to deceive the message receiving device. The man-in-the-middle attack refers to the attacker intercepting and tampering with the message in the network in an attempt to forge a valid ring signature. Social engineering attack refers to obtaining information about the ring members through social engineering means to infer the identity of the actual sender of the message. The intensity of the attack is a measure of the degree of resources invested by the attacker, such as computing power, bandwidth, etc. The attack frequency can refer to the number of attacks launched per unit time. The attack duration refers to the length of time each attack lasts. The attack tool refers to a security testing tool, and the tool technology can refer to attack technology and strategy, such as deep packet inspection, machine learning algorithm, etc. The attack intensity can include high, medium and low. The attack frequency can be once a minute, once an hour, once a day, once a week, etc. This embodiment can use an automated testing framework to automatically perform simulated attacks according to the above settings and record the attack results.

[0119] Step a422: Calculate the success probability of each attack type using the simulated attack model.

[0120] Exemplarily, this embodiment can be repeated for multiple experiments to obtain the following success rates: the success rate of traffic analysis attack is 0.2, the success rate of behavior pattern attack is 0.1, the success rate of replay attack is 0.05, the success rate of man-in-the-middle attack is 0.3, and the success rate of social engineering attack is 0.15.

[0121] Step a423: weighted sum the success probabilities of all attack types to obtain the total probability of the ring member combination being successfully attacked. In this embodiment, the weights of different attack types are dynamically adjusted according to specific application scenarios to reflect their relative importance.

[0122] By executing steps a421 to a423, the embodiment of the present application can more comprehensively evaluate the security of the ring member combination by introducing multiple attack types, avoiding the limitations of a single attack type. By simulating the attack model to calculate the success probability of each attack type and performing weighted summation, a quantitative assessment of the risk is achieved. The total probability obtained by weighted summation can guide the system to take targeted defense measures to enhance the robustness and anti-attack capability of the system. For example, for attack types with high success rates, corresponding protective measures can be strengthened as a priority. Therefore, this embodiment improves the security and reliability of the method by introducing multi-dimensional attack simulation, success probability calculation and risk quantification assessment.

[0123] Step a43, sort the individuals in the population according to the fitness function, and perform selection operation, crossover operation and mutation operation to obtain the next generation population; the population is the initial population when the iteration number is 1, and is the next generation population when the iteration number is other values ​​greater than 1.

[0124] Step a44 determines whether the preset stop iteration condition is reached. If not, the sorting, selection, crossover and mutation operations in step a43 and step a44 are repeatedly performed until the preset stop iteration condition is reached. The preset stop iteration condition is that the maximum number of iterations is reached, or the fitness function value of the best individual in the last generation of the population is greater than or equal to the preset function threshold, or the fitness change degree of the population is less than the preset change threshold. The preset stop iteration condition (such as the maximum number of iterations, fitness threshold, fitness change degree) allows the system to flexibly adjust the termination condition according to specific needs, ensuring that excessive calculation is avoided while achieving the optimal solution.

[0125] By executing steps a41 to a44, the embodiment of the present application ensures the diversity of the ring member combination according to the diversity quantification result in the defined fitness function. This not only improves anonymity, but also makes it more difficult for attackers to identify the actual message sending device by analyzing the behavior patterns of the ring members. This embodiment introduces the probability of the ring member combination being successfully attacked as part of the fitness function, thereby enhancing the anti-attack capability. By simulating multiple attack types and calculating their success probabilities, this embodiment can better resist potential security threats. Through selection operations, crossover operations, and mutation operations, the genetic algorithm can continuously optimize the population in multiple generations of iterations to find the best ring member combination. This method not only improves search efficiency, but also reduces unnecessary waste of computing resources.

[0126] Figure 2 A structural diagram of a 5G message transmission system based on privacy protection provided in an embodiment of the present application is as follows: Figure 2 As shown, the system includes:

[0127] The encryption module 21 is used to encrypt the content of the 5G message to be sent and generate an encrypted message.

[0128] The segmentation generation module 22 is used to segment the encrypted message into multiple encrypted message segments, generate corresponding obfuscation information for each encrypted message segment through a pseudo-random number generator, and encrypt the sensitive metadata using homomorphic encryption technology to form a first data packet including the encrypted message segments, the obfuscation information and the encrypted sensitive metadata; the number of the first data packets is the same as the number of the encrypted message segments.

[0129] The determination module 23 is used to select a group of ring members from the target candidate pool by applying the ring member selection optimization algorithm in combination with the zero-knowledge proof result corresponding to each first data packet, determine the anonymous verification information corresponding to each first data packet in combination with the group of ring members, and generate a second data packet containing the anonymous verification information; all second data packets together constitute a set of data packets to be transmitted; the anonymity contribution value of the candidate members in the target candidate pool is greater than or equal to the preset contribution threshold, and the anonymity contribution value is calculated based on the activity level and association strength of the candidate members.

[0130] The allocation module 24 is used to determine multiple transmission paths by using a multi-path selection algorithm in combination with a routing selection strategy, and to allocate tasks to each transmission path using a distributed hash table based on a set of data packets to be transmitted to obtain an allocation result.

[0131] The transmission module 25 is used to disperse the transmission of the set of data packets to be transmitted according to the allocation result, so that after the message receiving device receives all the second data packets, it uses a threshold decryption scheme to reorganize and decrypt all the second data packets based on the security keys pre-exchanged and negotiated through the multi-party computing protocol to remove obfuscated information and restore the 5G message content.

[0132] Figure 2 The 5G message transmission system based on privacy protection can be executed Figure 1 The implementation principle and technical effect of the 5G message transmission method based on privacy protection described in the illustrated embodiment will not be repeated. The specific manner in which each module and unit performs operations in the 5G message transmission system based on privacy protection in the above embodiment has been described in detail in the embodiment of the method, and will not be elaborated here.

[0133] In one possible design, Figure 2 The privacy protection-based 5G message transmission system of the illustrated embodiment can be implemented as a computing device, such as Figure 3 As shown, the computing device may include a storage component 31 and a processing component 32 .

[0134] The storage component 31 stores one or more computer instructions, wherein the one or more computer instructions are called and executed by the processing component 32 .

[0135] The processing component 32 is used to: encrypt the 5G message content to be sent to generate an encrypted message; divide the encrypted message into multiple encrypted message segments, generate corresponding obfuscation information for each encrypted message segment through a pseudo-random number generator, and encrypt the sensitive metadata using homomorphic encryption technology to form a first data packet including the encrypted message segments, the obfuscation information and the encrypted sensitive metadata; the number of the first data packets is the same as the number of the encrypted message segments; in combination with the zero-knowledge proof result corresponding to each first data packet, a group of ring members are selected from the target candidate pool using a ring member selection optimization algorithm, anonymous verification information corresponding to each first data packet is determined in combination with the group of ring members, and a second data packet containing the anonymous verification information is generated; the candidate in the target candidate pool The anonymity contribution value of the member is greater than or equal to the preset contribution threshold, and the anonymity contribution value is calculated based on the activity level and association strength of the candidate member; all second data packets together constitute a set of data packets to be transmitted; a multi-path selection algorithm is used in combination with a routing selection strategy to determine multiple transmission paths, and based on the set of data packets to be transmitted, a distributed hash table is used to assign tasks to each transmission path to obtain an assignment result; according to the assignment result, the set of data packets to be transmitted is dispersedly transmitted, so that after the message receiving device receives all the second data packets, based on the security keys pre-exchanged and negotiated through the multi-party computing protocol, a threshold decryption scheme is used to reorganize and decrypt all the second data packets to remove obfuscated information and restore the 5G message content.

[0136] The processing component 32 may include one or more processors to execute computer instructions to complete all or part of the steps in the above method. Of course, the processing component may also be implemented by one or more application-specific integrated circuits (ASIC), digital signal processors (DSP), digital signal processing devices (DSPD), programmable logic devices (PLD), field programmable gate arrays (FPGA), controllers, microcontrollers, microprocessors or other electronic components to perform the above method.

[0137] The storage component 31 is configured to store various types of data to support operations at the terminal. The storage component can be implemented by any type of volatile or non-volatile storage device or a combination thereof, such as random access memory (RAM), static random access memory (SRAM), electrically erasable programmable read-only memory (EEPROM), erasable programmable read-only memory (EPROM), programmable read-only memory (PROM), read-only memory (ROM), magnetic memory, flash memory, magnetic disk or optical disk.

[0138] Of course, the computing device may also include other components, such as input / output interfaces, display components, communication components, etc.

[0139] The input / output interface provides an interface between the processing component and the peripheral interface module, which may be an output device, an input device, etc.

[0140] The communication component is configured to facilitate, among other things, wired or wireless communications between the computing device and other devices.

[0141] Among them, the computing device can be a physical device or an elastic computing host provided by a cloud computing platform, etc. In this case, the computing device can refer to a cloud server, and the above-mentioned processing components, storage components, etc. can be basic server resources rented or purchased from the cloud computing platform.

[0142] The present application also provides a computer storage medium storing a computer program, wherein the computer program can achieve the above-mentioned Figure 1 The 5G message transmission method based on privacy protection of the illustrated embodiment.

[0143] Those skilled in the art can clearly understand that, for the convenience and brevity of description, the specific working processes of the systems and units described above can refer to the corresponding processes in the aforementioned method embodiments and will not be repeated here.

[0144] The system embodiment described above is merely illustrative, wherein the units described as separate components may or may not be physically separated, and the components shown as units may or may not be physical units, that is, they may be located in one place, or they may be distributed on multiple network units. Some or all of the modules may be selected according to actual needs to achieve the purpose of the solution of this embodiment. Those of ordinary skill in the art may understand and implement it without creative work.

[0145] Through the description of the above implementation methods, those skilled in the art can clearly understand that each implementation method can be implemented by means of software plus a necessary general hardware platform, and of course, can also be implemented by hardware. Based on this understanding, the above technical solution is essentially or the part that contributes to the prior art can be embodied in the form of a software product, and the computer software product can be stored in a computer-readable storage medium, such as ROM / RAM, a disk, an optical disk, etc., including a number of instructions for a computer device (which can be a personal computer, a server, or a network device, etc.) to execute the methods described in each embodiment or some parts of the embodiments.

[0146] Finally, it should be noted that the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit it. Although the present application has been described in detail with reference to the aforementioned embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the aforementioned embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A 5G message transmission method based on privacy protection, characterized in that: include: Encrypt the content of the 5G message to be sent to generate an encrypted message; The encrypted message is divided into a plurality of encrypted message segments, corresponding obfuscation information is generated for each encrypted message segment by a pseudo-random number generator, and the sensitive metadata is encrypted by applying homomorphic encryption technology to form a first data packet including the encrypted message segments, the obfuscation information and the encrypted sensitive metadata; the number of the first data packet is the same as the number of the encrypted message segments; In combination with the zero-knowledge proof result corresponding to each first data packet, a group of ring members are selected from the target candidate pool by applying the ring member selection optimization algorithm, anonymous verification information corresponding to each first data packet is determined in combination with the group of ring members, and a second data packet containing the anonymous verification information is generated; all the second data packets together constitute a set of data packets to be transmitted; The anonymity contribution value of the candidate members in the target candidate pool is greater than or equal to a preset contribution threshold, and the anonymity contribution value is calculated based on the activity level and association strength of the candidate members; Using a multi-path selection algorithm and combining it with a routing selection strategy to determine multiple transmission paths, and based on the set of data packets to be transmitted, using a distributed hash table to perform task allocation for each transmission path to obtain an allocation result; The set of data packets to be transmitted are transmitted in a dispersed manner according to the allocation result, so that after the message receiving device receives all the second data packets, based on the security keys pre-exchanged and negotiated through the multi-party computing protocol, all the second data packets are reorganized and decrypted using a threshold decryption scheme to remove obfuscated information and restore the 5G message content.

2. The method according to claim 1, characterized in that The method combines the zero-knowledge proof result corresponding to each first data packet, selects a group of ring members from the target candidate pool by applying the ring member selection optimization algorithm, determines the anonymous verification information corresponding to each first data packet by combining the group of ring members, and generates a second data packet containing the anonymous verification information, including: Using a zero-knowledge proof mechanism, according to predefined protocol rules, a corresponding zero-knowledge proof result is generated for each of the first data packets; Based on the zero-knowledge proof result, a ring member selection optimization algorithm is applied to select a group of ring members from a target candidate pool to form a ring member combination, wherein the ring member combination includes an actual message sending device and a non-actual message sending device; Based on the private key of the actual message sending device and the public key of the non-actual message sending device, an anonymous verification message is generated using the ring signature algorithm; The anonymous verification message is added to the first data packet to form a second data packet.

3. The method according to claim 2, characterized in that The step of selecting a group of ring members from a target candidate pool by applying a ring member selection optimization algorithm based on the zero-knowledge proof result includes: According to the system registration information and the device communication history records, an initial candidate pool including all potential message sending devices is established, and potential message sending devices known to be offline or unable to participate in signing are removed from the initial candidate pool to obtain an intermediate candidate pool; the initial candidate pool includes actual message sending devices, and the actual message sending devices are identified to be retained in the intermediate candidate pool; Determine the activity level of each candidate member in the intermediate candidate pool and the strength of association between the candidate member and the actual message sending device according to the zero-knowledge proof result, and calculate the anonymity contribution value of each candidate member in the intermediate candidate pool according to the activity level and the strength of association; Screening candidate members whose anonymity contribution value is greater than or equal to a preset contribution threshold to form a target candidate pool; The number of ring members is determined according to predefined security parameters, and a group of ring members is selected from the target candidate pool by applying a ring member selection optimization algorithm according to the number of ring members to form a ring member combination.

4. The method according to claim 3, characterized in that The calculating, according to the activity level and the association strength, the anonymity contribution value of each candidate member in the intermediate candidate pool includes: For each candidate member in the intermediate candidate pool, the activity level of the candidate member is quantified based on the number of active days, average online time and number of communications, and a historical activity frequency value is obtained; Constructing hidden Markov models corresponding to the number of times of jointly participating in communication, the strength of social relationship and the proximity of geographical location respectively, using the corresponding hidden Markov models to respectively calculate the pattern similarity, social relationship strength and geographical location proximity of the candidate members and the actual message sending device jointly participating in communication, and weightedly summing the pattern similarity, social relationship strength and geographical location proximity of the candidate members and the actual message sending device jointly participating in communication to quantify the association strength of the candidate members to obtain an association value; The weighted sum of the historical activity frequency value and the association value is determined as the anonymity contribution value of the candidate member.

5. The method according to claim 3, characterized in that: The step of selecting a group of ring members from the target candidate pool by applying a ring member selection optimization algorithm according to the number of ring members includes: Generate an initial population according to the number N of the ring members, each individual in the initial population represents a ring member combination, and the ring member combination includes 1 actual message sending device and N-1 non-actual message sending devices; The fitness function is defined based on the sum of the anonymity contribution values ​​of all ring members, the quantitative results of the diversity of the ring member combination, and the probability of the ring member combination being successfully attacked. The fitness function uses the following formula: ； in, is the fitness value of the ring member combination, Is the first member of the ring The anonymity contribution value of each ring member; It represents the sum of the anonymity contribution values ​​of all ring members in the ring member combination, and N represents the number of ring members; It is the quantitative result of the diversity of the ring member combinations; is the probability that a combination of ring members is successfully attacked; is the weight coefficient of the corresponding item, which is used to balance the influence of different factors; The individuals in the population are sorted according to the fitness function, and selection operations, crossover operations and mutation operations are performed to obtain the next generation population; the population is the initial population when the number of iterations is 1, and is the next generation population when the number of iterations is other values ​​greater than 1; Determine whether the preset stop iteration condition is reached. If not, repeat the sorting, selection, crossover and mutation operations, as well as the judgment operation, until the preset stop iteration condition is reached. The preset stop iteration condition is that the maximum number of iterations is reached, or the fitness function value of the best individual in the last generation of the population is greater than or equal to the preset function threshold, or the fitness change degree of the population is less than the preset change threshold.

6. The method according to claim 5, characterized in that The process of obtaining the probability of a ring member combination being successfully attacked includes: For simulated attack scenarios of multiple attack types, corresponding attack parameters, attack tools, tool techniques and attack targets are set to build a simulated attack model; the multiple attack types include traffic analysis attacks, behavior pattern attacks, replay attacks, man-in-the-middle attacks and social engineering attacks; the attack parameters include: attack intensity, attack frequency and attack duration; the attack target is at least one of an actual message sending device and a non-actual message sending device; Calculating the success probability of each attack type using the simulated attack model; The success probabilities of all attack types are weighted and summed to obtain the total probability of a ring member combination being successfully attacked.

7. The method according to claim 2, characterized in that The method uses a ring signature algorithm to generate an anonymous verification message based on the private key of the actual message sending device and the public key of the non-actual message sending device, including: Obtain the private key of the actual message sending device and the public key of the non-actual message sending device; The public key of the non-actual message sending device is hashed in combination with the timestamp to obtain a corresponding hash value; if there are multiple non-actual message sending devices, all hash values ​​are linked to obtain a chain hash structure; Based on the private key of the actual message sending device and the chain hash structure, an anonymous verification message is generated using a ring signature algorithm.

8. A 5G message transmission system based on privacy protection, characterized in that: include: An encryption module is used to encrypt the content of the 5G message to be sent and generate an encrypted message; a segmentation generation module, configured to segment the encrypted message into a plurality of encrypted message segments, generate corresponding obfuscation information for each encrypted message segment by a pseudo-random number generator, and encrypt the sensitive metadata by applying homomorphic encryption technology to form a first data packet including the encrypted message segments, the obfuscation information and the encrypted sensitive metadata; the number of the first data packets is the same as the number of the encrypted message segments; A determination module, used to select a group of ring members from a target candidate pool by applying a ring member selection optimization algorithm in combination with a zero-knowledge proof result corresponding to each first data packet, determine the anonymous verification information corresponding to each first data packet in combination with the group of ring members, and generate a second data packet containing the anonymous verification information; all the second data packets together constitute a data packet set to be transmitted; The anonymity contribution value of the candidate members in the target candidate pool is greater than or equal to a preset contribution threshold, and the anonymity contribution value is calculated based on the activity level and association strength of the candidate members; An allocation module is used to determine multiple transmission paths by using a multi-path selection algorithm in combination with a routing selection strategy, and based on the set of data packets to be transmitted, use a distributed hash table to perform task allocation for each transmission path to obtain an allocation result; The transmission module is used to disperse the set of data packets to be transmitted according to the allocation result, so that after the message receiving device receives all the second data packets, it uses a threshold decryption scheme to reorganize and decrypt all the second data packets based on the security keys pre-exchanged and negotiated through the multi-party computing protocol to remove obfuscated information and restore the 5G message content.

9. A computing device, characterized in that It includes a processing component and a storage component; the storage component stores one or more computer instructions; the one or more computer instructions are used to be called and executed by the processing component to implement a 5G message transmission method based on privacy protection as described in any one of claims 1 to 7.

10. A computer storage medium, characterized in that: A computer program is stored, and when the computer program is executed by a computer, a 5G message transmission method based on privacy protection as described in any one of claims 1 to 7 is implemented.

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