Network edge calculation method and communication device

Abstract

The invention discloses a network edge calculation method and a communication device, and relates to the technical field of network communication, and the method comprises the following calculation steps: inputting original data into a calculation processing module, and outputting processed data, encrypted data, a hash value of the encrypted data, an authentication code of a message and a verification result. And transmitting the encrypted data, the hash value of the encrypted data, the authentication code of the message and the verification result to a cloud server. The method has the advantages that the received data is changed firstly, so that the encryption efficiency and security of the data are improved, the data are encrypted in an encryption mode, the confidentiality of the data is guaranteed, the integrity verification of the data is carried out through the hash function and the message authentication code, and the security of the data is improved. According to the data transmission method and device, the data are ensured not to be tampered in the transmission process, all-directional protection of the data is achieved, meanwhile, the received data are verified in a verification mode so as to ensure the authenticity of the data, and dual guarantee of data transmission and verification is achieved.

Description

Technical Field

[0001] The present invention relates to the field of network communication technology, and in particular to a network edge computing method and a communication device. Background Art

[0002] With the rapid development of Internet of Things technology, multi-access edge computing has been widely used as an innovative network architecture. Multi-access edge computing deploys computing functions close to terminal devices to significantly reduce data transmission delays, improve service response speeds, and enhance overall network performance.

[0003] However, in the existing multi-access edge computing, when the multi-access edge computing device performs computing tasks on the network side, it needs to interact with the core network for data. This form of data interaction is particularly vulnerable when processing sensitive information, and may lead to security risks of data leakage and tampering, thereby reducing the security of internal data. In addition, the multi-access edge computing architecture lacks effective data encryption and integrity verification mechanisms during data interaction, which may increase the risk of sensitive information being stolen during transmission. Summary of the invention

[0004] The purpose of the present invention is to provide a network edge computing method and a communication device to solve the problems raised in the above-mentioned background technology.

[0005] To achieve the above object, the present invention provides the following technical solution: a network edge computing method, comprising the following computing steps: The first step is to obtain the data sent by the receiver through the data acquisition module, denoise, smooth and normalize the data sent by the receiver based on the data processing module, perform data cutting and data screening on the data sent by the receiver, and output the original data; Step 2: Input the original data into the calculation processing module, output the processed data, encrypted data, hash value of the encrypted data, authentication code of the message and verification result, and transmit the encrypted data, hash value of the encrypted data, authentication code of the message and verification result to the cloud server; Step 3: Compare the verification result with the verification result provided by the sender on the cloud server. After the verification is passed, decrypt the encrypted data, output the original data, and store the decrypted original data; Step 4: Continuously monitor network edge computing nodes and network security performance through the monitoring module.

[0006] Optionally, the calculation processing module includes: a data transformation submodule, an encryption verification submodule, a circulation submodule and a verification submodule.

[0007] Optionally, the data conversion submodule processing process is as follows: ; in: T1 represents the processed data; T2 represents the original data; α represents the adjustment constant, β represents the transformation amplitude constant, γ represents the influence multiplier of the sine function, ɛ represents the function parameter value, θ represents the influence multiplier of the cosine function, and μ represents the transformation parameter; They represent the sine and cosine functions respectively, and introduce trigonometric functions into T1 to increase the complexity; Based on the original data T2, the complexity of the original data T2 is increased by inputting α, β, and γ, and the sine function and cosine function It is applied to improve the randomness of the original data T2 so as to transform the original data T2 and output the processed data T1.

[0008] Optionally, the encryption check submodule processing process is as follows: ; in: Y represents the encrypted data, U represents the hash value of the encrypted data, and AYU represents the authentication code of the message; len(T1) represents the encryption key, E K represents an encryption function, using the encryption key K to encrypt T1, ⊕ represents an XOR operation, and Hash represents a hash function; len(T1) represents the length of the processed data T1, b is the transformation parameter of Y, c and d are the check parameters of Y, and mod(len(Y), C) represents the modulus operation on the encrypted data Y; HMAC k represents a hash message authentication code function based on k, Encode represents an encoding function, Encode(U) represents the encoding of the hash value U of the encrypted data, and len(Y) represents the length of the encrypted data Y; The processed data T1 is encrypted based on the encryption key K and the encryption function E K Encrypt and output the encrypted data Y; The encrypted data Y is used to calculate the hash value U of the encrypted data Y based on the hash function Hash; Through the K-based hash message authentication code function HMAC k The encrypted data Y and the hash value U of the encrypted data are calculated to output the message authentication code AYU.

[0009] Optionally, the loop submodule processing process is as follows: enter: ; Set the termination condition: (1) Set the number of iterations n≤50;

[0010] (2) ; Output: When any of (1) and (2) is satisfied, the loop terminates and the convergence condition is achieved; in: β new represents the new transformation amplitude constant; β low Represents the transformation amplitude constant in the data transformation submodule; Hash(U) represents the result value of the function call of U; e represents the adjustment coefficient; n represents the number of cycles; p represents the contrast threshold; The result value Hash(U) of the function call of U and the adjustment coefficient e are used as the influencing factors of the transformation amplitude constant β, and input β low Output β new , and β new The transformation amplitude constant β in the data transformation submodule is replaced to adjust the processed data T1, and the two conditional factors n and p are used as the termination conditions.

[0011] Optionally, the verification submodule processes as follows: ; in: RA indicates the verification result; Hash(U) represents the result of hash operation on encrypted data, and L represents the adjustment divisor; ou represents the adjustment addend, f represents the multiplier of T1, and (mod(T1*f),ou) represents the modulo function of T1; The encrypted data Y, the hash value U of the encrypted data and the authentication code AYU of the message are packaged and transmitted to the cloud server through a secure communication protocol. The hash value of the received encrypted data Y is calculated using the same hash algorithm and compared with the hash value provided by the sender to verify the integrity of the data. Based on the adjusted divisor L, the result of the hash operation of the encrypted data Hash(U), the length of the encrypted data Y len(Y), and the modulus function of T1 (mod(T1*f),ou), the verification result RA is output, and the calculated verification result RA is compared with the verification result provided by the sender to confirm the authenticity of the data; After the integrity and authenticity verification is passed, the encrypted data Y is decrypted to obtain the original data T2. Finally, the decrypted data is stored, analyzed and processed according to specific application requirements.

[0012] A communication device for a network edge computing method comprises a data acquisition module, a data processing module, a computing processing module and a monitoring module.

[0013] Optionally, the data processing module performs denoising, smoothing and normalization on the data sent by the receiver to ensure the accuracy and completeness of the data, and performs data cropping and data screening on the data sent by the receiver to output the original data to reduce the amount of data transmission.

[0014] Compared with the prior art, the present invention has the following beneficial effects: 1. The present invention substitutes the original data into the data transformation submodule and outputs the processed data. The data transformation submodule increases the complexity and randomness of the original data through mathematical changes, thereby making unauthorized access more difficult. The processed data plays an excellent data preprocessing role in the network edge computing method, making it difficult for attackers to directly obtain information about the original data through statistical analysis and other means, thereby improving security and stability.

[0015] 2. The present invention substitutes the processed data into the encryption check submodule, outputs the encrypted data, the hash value of the encrypted data and the authentication code of the message. The encryption check submodule combines the two mechanisms of encryption and integrity verification, thereby providing more comprehensive data protection. The calculation of the authentication code of the message takes into account multiple factors, making the verification process more rigorous and reliable. The encrypted data Y ensures the confidentiality of the data, that is, unauthorized users cannot directly read the data content. The hash value U of the encrypted data facilitates subsequent integrity verification. The authentication code AYU of the message is generated in combination with the hash value and the key to verify the integrity and authenticity of the data.

[0016] 3. The present invention substitutes the hash value U of the encrypted data into the loop submodule and outputs β new , by β new Replace β in the data transformation submodule to achieve the purpose of iterative loop. By iteratively updating β, the overall system can respond to various challenges more flexibly and intelligently, which can not only improve the dynamic adaptability and security of the system but also optimize the system performance. Through iterative updates, the system can regularly change the key, thereby enhancing the security of data transmission and storage.

[0017] 4. The present invention outputs a verification result by substituting the encrypted data, the hash value of the encrypted data, the authentication code of the message and the processed data into the verification submodule. The verification result can be used to confirm whether the received data is complete and has not been tampered with. The verification result reflects the comprehensive characteristics of the encrypted data and the hash value of the encrypted data. This submodule provides a more comprehensive verification mechanism. The verification result can easily reduce the false positives and negative negatives that may be caused by a single verification mechanism. The correctness of the verification result is directly related to the integrity and authenticity of the data. Only when the value is correct can it be confirmed that the received data is safe and reliable, thereby enhancing the security of the entire system. BRIEF DESCRIPTION OF THE DRAWINGS

[0018] Figure 1 A flowchart of the steps of the network edge computing method; Figure 2 This is a schematic diagram of the overall structure of the communication device of the network edge computing method; Figure 3 A schematic diagram of the structure of the computing processing module. DETAILED DESCRIPTION

[0019] The following will be combined with the drawings in the embodiments of the present invention to clearly and completely describe the technical solutions in the embodiments of the present invention. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without creative work are within the scope of protection of the present invention.

[0020] Regarding this network edge computing method, it is different from the existing network edge computing methods. The existing network edge computing methods may lack effective data encryption and integrity verification mechanisms during data interaction, which makes sensitive information easy to be stolen or tampered with during transmission, resulting in poor security. The algorithm module of this network edge computing method transforms the data, thereby improving the encryption efficiency and security of the data, and encrypts the data to ensure the confidentiality of the data during transmission, thereby improving security.

[0021] Example 1: Please refer to Figures 1 to 3 , this implementation provides a network edge computing method, which has the following steps: The first step is to obtain the data sent by the receiver through the data acquisition module, denoise, smooth and normalize the data sent by the receiver based on the data processing module, perform data cutting and data screening on the data sent by the receiver, and output the original data; Step 2: Input the original data into the calculation processing module, output the processed data, encrypted data, hash value of the encrypted data, authentication code of the message and verification result, and transmit the encrypted data, hash value of the encrypted data, authentication code of the message and verification result to the cloud server; Step 3: Compare the verification result with the verification result provided by the sender on the cloud server. After the verification is passed, decrypt the encrypted data, output the original data, and store the decrypted original data; Step 4: Continuously monitor network edge computing nodes and network security performance through the monitoring module; The calculation processing module includes: a data transformation submodule, an encryption check submodule, a circulation submodule and a verification submodule.

[0022] In this embodiment: The network edge computing method proposed in the present invention achieves the security goal in the data interaction process by combining multiple submodules in the computing processing module. This not only solves the data security problems existing in the existing multi-access edge computing, provides users with faster services and achieves better network performance architecture, but also improves the flexibility of the system and provides new ideas and technical support for the development of Internet of Things technology; The monitoring module monitors and ensures the performance of network edge computing nodes and network security. It can analyze and determine performance problems, resource allocation problems and vulnerabilities in the network, and then make timely adjustments to ensure the stability of this network edge computing method system. The performance monitoring software Prometheus is used to collect and process system performance data in real time. The log analysis tool is used to analyze system logs to identify potential problems and abnormal behaviors. Network monitoring equipment such as network traffic analyzers and intrusion detection systems are used to monitor network performance and security. The data visualization tool Tableau is used to intuitively display the analysis results in the form of charts, dashboards, etc. for management personnel to view; In addition, the data is preprocessed and encrypted on the edge side, which reduces the amount of data interacting with the core network, thereby reducing the delay and bandwidth consumption of data transmission. At the same time, through the optimization algorithm and distributed computing technology, the processing power and efficiency of edge network computing devices are improved. Compared with the existing edge network computing system, since data needs to interact with the core network, the delay and bandwidth consumption of data transmission are increased, especially when processing large-scale data, which may lead to performance bottlenecks of edge network computing devices.

[0023] See also Figures 1 to 3 , the data transformation submodules are as follows: ; in: T1 represents the processed data; T2 represents the original data; α represents the adjustment constant, β represents the transformation amplitude constant, γ represents the influence multiplier of the sine function, ɛ represents the function parameter value, θ represents the influence multiplier of the cosine function, and μ represents the transformation parameter; They represent the sine and cosine functions respectively, and introduce trigonometric functions into T1 to increase the complexity; Based on the original data T2, the complexity of the original data T2 is increased by inputting α, β, and γ, and the sine function and cosine function It is applied to improve the randomness of the original data T2 so as to transform the original data T2 and output the processed data T1.

[0024] In this embodiment: α represents an adjustment constant, or it may be a dynamic value based on specific rules, such as a part of a timestamp, a hash value of a user ID, etc. In some cases, it may be a key fragment or a random number generated during the encryption process. β represents a transformation amplitude constant, which is used to control the amplitude or direction of the transformation. It may also be a part of an encryption key, and a value dynamically calculated according to data attributes. γ represents an influence multiplier of a sine function, which may be used to adjust the influence of items related to α or β on the transformation result. ɛ represents a function parameter value. ɛ is used in combination with the trigonometric function sin to introduce periodic changes to the transformation. It may also be a value representing time, number of iterations, data block index, etc. It may also be a key fragment or a random number to increase the unpredictability of the transformation. θ represents an influence multiplier of a cosine function, which is used to multiply the output of a cosine function to further adjust the transformation result. μ represents a transformation parameter. μ is used as an input of a cosine function to introduce another periodic change to the transformation. μ may be a part of a timestamp, a random number, or the output of a specific algorithm to introduce dynamics. This module generates a processed data T1 by performing a series of mathematical transformations on the original data T2, thereby increasing the complexity and randomness of the data, so that the subsequent encryption process is more secure. The processed data T1 is more difficult to directly analyze or predict than the original data T2. At the same time, due to the introduction of sine and cosine functions, the data changes are smoother and more difficult to predict, which helps to resist certain types of statistical analysis attacks. The complexity and randomness of the data are increased through mathematical changes, making unauthorized access more difficult. The processed data T1 plays an excellent data preprocessing role in the network edge computing method, making it difficult for attackers to directly obtain information about the original data through statistical analysis and other means, and the processed data T1 is more suitable for encryption algorithms, thereby improving the efficiency and security of encryption.

[0025] See also Figures 1 to 3 , the encryption check submodule is as follows: ; in: Y represents the encrypted data, U represents the hash value of the encrypted data, and AYU represents the authentication code of the message; K represents the encryption key, E K represents an encryption function, using the encryption key K to encrypt T1, ⊕ represents an XOR operation, and Hash represents a hash function; len(T1) represents the length of the processed data T1, b is the transformation parameter of Y, c and d are the check parameters of Y, and mod(len(Y), C) represents the modulus operation on the encrypted data Y; HMAC k represents a K-based hash message authentication code function, Encode represents an encoding function used to convert a hash value into a format suitable for HMAC processing, Encode(U) represents the encoding of the hash value U of the encrypted data to ensure that it is suitable for the input of the HMAC function, and len(Y) represents the length of the encrypted data Y; The processed data T1 is encrypted based on the encryption key K and the encryption function E K Encrypt and output the encrypted data Y; The encrypted data Y is used to calculate the hash value U of the encrypted data Y based on the hash function Hash; Through the K-based hash message authentication code function HMAC k The encrypted data Y and the hash value U of the encrypted data are calculated to output the message authentication code AYU.

[0026] In this embodiment: by encryption function E K The combination of the hash function ensures the confidentiality of the processed data T1. At the same time, the combination of the hash value and the data length increases the complexity and security of encryption. By calculating the hash value U of the encrypted data and the authentication code AYU of the message, it can be verified whether the data has been tampered with during transmission. The calculation of AYU also takes into account the encoding of the hash value and the length of the key, which further enhances the reliability of verification. This submodule combines encryption and integrity verification mechanisms to provide more comprehensive data protection. The calculation of AYU takes into account multiple factors, making the verification process more rigorous and reliable. The encrypted data Y ensures the confidentiality of the data, that is, unauthorized users cannot directly read the data content. The hash value U of the encrypted data is used for subsequent integrity verification. The message authentication code AYU is generated by combining the hash value and the key to verify the integrity and authenticity of the data. The encrypted data Y ensures the confidentiality of the data and prevents it from being stolen or leaked during transmission. And through U and AYU, the receiver can verify that the received data is complete and has not been tampered with, which helps prevent security threats such as man-in-the-middle attacks.

[0027] See also Figures 1 to 3 , the loop submodule is as follows: enter: ; Set the termination condition: (1) Set the number of iterations n≤50;

[0028] (2) ; Output: When any of (1) and (2) is satisfied, the loop terminates and the convergence condition is achieved; in: β new represents the new transformation amplitude constant; β low Represents the transformation amplitude constant in the data transformation submodule; Hash(U) represents the result value of a function call of U, which receives U as input and returns a value; e represents the adjustment coefficient; n represents the number of cycles; p represents the contrast threshold; The result value Hash(U) of the function call of U and the adjustment coefficient e are used as the influencing factors of the transformation amplitude constant β, and input β low Output β new , and β new The transformation amplitude constant β in the data transformation submodule is replaced to adjust the processed data T1, and the two conditional factors n and p are used as the termination conditions.

[0029] In this embodiment: by iteratively updating β, the system can adjust its internal parameters according to the real-time situation to better adapt to these changes. Iterative updating of β can be used as part of an encryption or security strategy. β is part of the encryption key or is used to generate the encryption key. Then, through iterative updating, the system can regularly replace the key, thereby enhancing the security of data transmission and storage. The update of β can also be combined with security mechanisms such as data desensitization and access control to further improve the security of the system. By iteratively updating β, the system can continuously optimize its internal algorithms and parameter configurations to improve the execution speed and accuracy of computing tasks. This is particularly important for application scenarios that require low latency and high reliability; Multi-access edge computing refers to providing users with faster services and better network performance by deploying computing functions close to the device side. Different from the existing multi-access edge computing, which usually relies on static configuration or simple feedback mechanism to adjust system parameters, this method may not be able to quickly adapt to changes in network conditions or meet complex security requirements. This method iteratively updates β, and the system can respond to various challenges more flexibly and intelligently. Iterative update of β plays an important role and advantage in network edge computing. It can not only improve the dynamic adaptability and security of the system, but also optimize system performance. Through iterative update of β, the multi-access edge computing system can respond to changes in network conditions and changes in user needs more intelligently, thereby providing more efficient, reliable and secure services.

[0030] See also Figures 1 to 3 , the verification submodules are as follows: ; in: RA represents the verification result, which can also be expressed as the verification pass mark, score, and decision value; Hash(U) represents the result of hash operation on encrypted data, and L represents the adjustment divisor; ou represents the adjustment addend, which is used to further adjust the result, f represents the multiplier of T1, and (mod(T1*f),ou) represents the modulo function of T1; The encrypted data Y, the hash value U of the encrypted data and the authentication code AYU of the message are packaged and transmitted to the cloud server through a secure communication protocol. The hash value of the received encrypted data Y is calculated using the same hash algorithm and compared with the hash value provided by the sender to verify the integrity of the data. Based on the adjusted divisor L, the result of the hash operation of the encrypted data Hash(U), the length of the encrypted data Y len(Y), and the modulus function of T1 (mod(T1*f),ou), the verification result RA is output, and the calculated verification result RA is compared with the verification result provided by the sender to confirm the authenticity of the data; After the integrity and authenticity verification is passed, the encrypted data Y is decrypted to obtain the original data T2. Finally, the decrypted data is stored, analyzed and processed according to specific application requirements.

[0031] In this embodiment: this submodule combines the encrypted data Y and the length len(Y) of the encrypted data Y to generate a verification result RA, which can be used to confirm whether the received data is complete and has not been tampered with. The verification result RA reflects the comprehensive characteristics of the encrypted data Y and the hash value U of the encrypted data. Only when the data is complete and has not been tampered with can the correct RA value be calculated. This submodule provides a more comprehensive verification mechanism. The verification result RA can reduce the false positives that may be caused by a single verification mechanism, that is, misjudging legal data as illegal, and the omissions that are misjudged as illegal data as legal. The correctness of the verification result RA is directly related to the integrity and authenticity of the data. Only when the RA value is correct can it be confirmed that the received data is safe and reliable, thereby enhancing the security of the entire system.

[0032] In the specific implementation process, multiple groups of sub-modules in the method are used to form an edge computing security method system. The original data T2 is substituted into the data transformation sub-module to output the processed data T1. The processed data T1 increases the complexity and randomness of the data, so that the subsequent encryption process is more secure. The sine and cosine functions are introduced to make the data changes smoother and more difficult to predict, which helps to resist certain types of statistical analysis attacks. The processed data T1 is substituted into the encryption check sub-module to output the encrypted data Y, the hash value U of the encrypted data and the authentication code AYU of the message. The confidentiality of the processed data T1 is ensured through the cooperation of the encryption function and the hash function, and the hash value is combined with the data length to increase the complexity and security of the encryption, and the hash value U of the encrypted data and the authentication code AYU of the message are calculated. , it can verify whether the data has been tampered with during the transmission process. The calculation of the authentication code AYU of the message also takes into account the encoding of the hash value and the length of the key, which further enhances the reliability of the verification. Then the encrypted data Y, the hash value U of the encrypted data, the authentication code AYU of the message and the processed data T1 are substituted into the verification submodule to output the verification result RA. The verification result RA can be used to confirm whether the received data is complete and has not been tampered with. The verification result RA reflects the comprehensive characteristics of the encrypted data Y and the hash value U of the encrypted data. Only when the data is complete and has not been tampered with can the correct RA value be calculated. Then, the module provides a more comprehensive verification mechanism. The verification result RA can reduce the false alarms that may be caused by a single verification mechanism, and the overall modules also have a loop form. By substituting the hash value U of the encrypted data into the loop submodule, β is output. new , by β newReplace β in the data transformation submodule to achieve the purpose of iterative loop. By iteratively updating β, the overall system can adjust its internal parameters according to the real-time situation to better adapt to these changes. Iterative update of β can be used as part of encryption and security strategy. β can be part of the encryption key and used to generate encryption key. Then, through iterative update, the system can regularly change the key, thereby enhancing the security of data transmission and storage. In summary, the multiple groups of submodules can cooperate with each other in calculation, and can also perform overall loops and iterations, so that the overall system has the effect of automatic optimization and update, and thus better adaptability.

[0033] Example 2: Please refer to Figure 1 , Figure 2 and Figure 3 , a communication device for a network edge computing method, comprising: a data acquisition module, a data processing module, a computing processing module and a monitoring module.

[0034] In this embodiment, the communication device of the network edge computing method integrates a data acquisition module, a data processing module, a computing processing module and a monitoring module, thereby improving the security, efficiency and reliability of data transmission through network edge computing technology, and the composition of multiple modules as a whole forms a complete process of data reception, processing, encryption, transmission and verification. The device can ensure the safe, efficient and reliable transmission of data in the edge network, and is suitable for various application scenarios that require high security and real-time transmission. The data processing module performs denoising, smoothing and normalization on the data sent by the receiver to ensure the accuracy and integrity of the data, and performs data clipping and data screening on the data sent by the receiver to output the original data to reduce the amount of data transmission.

[0035] In this embodiment, multiple processing is performed on the data to ensure the accuracy and validity of the data, thereby improving the efficiency and convenience of the calculation.

[0036] Although embodiments of the present invention have been shown and described, it will be appreciated by those skilled in the art that various changes, modifications, substitutions and variations may be made to the embodiments without departing from the principles and spirit of the present invention, and that the scope of the present invention is defined by the appended claims and their equivalents.

Claims

1. A network edge computing method, characterized in that: The calculation steps include: The first step is to obtain the data sent by the receiver through the data acquisition module, denoise, smooth and normalize the data sent by the receiver based on the data processing module, perform data cutting and data screening on the data sent by the receiver, and output the original data; Step 2: Input the original data into the calculation processing module, output the processed data, encrypted data, hash value of the encrypted data, authentication code of the message and verification result, and transmit the encrypted data, hash value of the encrypted data, authentication code of the message and verification result to the cloud server; Step 3: Compare the verification result with the verification result provided by the sender on the cloud server. After the verification is passed, decrypt the encrypted data, output the original data, and store the decrypted original data; Step 4: Continuously monitor network edge computing nodes and network security performance through the monitoring module.

2. The network edge computing method according to claim 1, characterized in that: The calculation processing module includes: a data transformation submodule, an encryption check submodule, a circulation submodule and a verification submodule.

3. The network edge computing method according to claim 2, characterized in that: The data conversion submodule processing process is as follows: ； in: T1 represents the processed data; T2 represents the original data; α represents the adjustment constant, β represents the transformation amplitude constant, γ represents the influence multiplier of the sine function, ɛ represents the function parameter value, θ represents the influence multiplier of the cosine function, and μ represents the transformation parameter; They represent the sine and cosine functions respectively, and introduce trigonometric functions into T1 to increase the complexity; Based on the original data t2, the complexity of the original data T2 is increased by the input of α, β, and γ, and the sine function and cosine function It is applied to improve the randomness of the original data T2 so as to transform the original data T2 and output the processed data T1.

4. The network edge computing method according to claim 3, characterized in that: The encryption check submodule processing process is as follows: ； in: Y represents the encrypted data, U represents the hash value of the encrypted data, and AYU represents the authentication code of the message; K represents the encryption key, E K represents an encryption function, using the encryption key K to encrypt T1, ⊕ represents an XOR operation, and Hash represents a hash function; len(T1) represents the length of the processed data T1, T1 is the transformation parameter of Y, c and d are the verification parameters of Y, and mod(len(Y), C) represents the modulus operation on the encrypted data Y; HMAC k represents a hash message authentication code function based on K, Encode represents an encoding function, Encode(U) represents the encoding of the hash value U of the encrypted data, and len(Y) represents the length of the encrypted data Y; The processed data T1 is encrypted based on the encryption key K and the encryption function E K Encrypt and output the encrypted data Y; The encrypted data Y is used to calculate the hash value U of the encrypted data Y based on the hash function Hash; Through the K-based hash message authentication code function HMAC k The encrypted data Y and the hash value U of the encrypted data are calculated to output the message authentication code AYU.

5. The network edge computing method according to claim 4, characterized in that: The processing of the loop submodule is as follows: enter: ; Set the termination condition: (1) Set the number of iterations n≤50; （2）、 ； Output: When any of (1) and (2) is satisfied, the loop terminates and the convergence condition is achieved; in: β new represents the new transformation amplitude constant; β low Represents the transformation amplitude constant in the data transformation submodule; Hash(U) represents the result value of the function call of U; e represents the adjustment coefficient; n represents the number of cycles; p represents the contrast threshold; The result value Hash(U) of the function call of U and the adjustment coefficient e are used as the influencing factors of the transformation amplitude constant β, and input β low Output β new , and β new The transformation amplitude constant β in the data transformation submodule is replaced to adjust the processed data T1, and the two conditional factors n and p are used as the termination conditions.

6. The network edge computing method according to claim 5, characterized in that: The verification submodule processing process is as follows: ； in: RA indicates the verification result; Hash(U) represents the result of hash operation on encrypted data, and L represents the adjustment divisor; ou represents the adjustment addend, f represents the multiplier of T1, and (mod(T1*f),ou) represents the modulo function of T1; The encrypted data Y, the hash value U of the encrypted data and the authentication code AYU of the message are packaged and transmitted to the cloud server through a secure communication protocol. The hash value of the received encrypted data Y is calculated using the same hash algorithm and compared with the hash value provided by the sender to verify the integrity of the data. Based on the adjusted divisor L, the result of the hash operation of the encrypted data Hash(U), the length of the encrypted data Y len(Y), and the modulus function of T1 (mod(T1*f),ou), the verification result RA is output, and the calculated verification result RA is compared with the verification result provided by the sender to confirm the authenticity of the data; After the integrity and authenticity verification is passed, the encrypted data Y is decrypted to obtain the original data T2. Finally, the decrypted data is stored, analyzed and processed according to specific application requirements.

7. A communication device for the network edge computing method according to claim 1, characterized in that: It includes a data acquisition module, a data processing module, a calculation processing module and a monitoring module.

8. The communication device of the network edge computing method according to claim 7, characterized in that: The data processing module performs denoising, smoothing and normalization on the data sent by the receiver to ensure the accuracy and integrity of the data, and performs data clipping and data screening on the data sent by the receiver to output the original data to reduce the amount of data transmission.

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