A load management terminal safe and reliable converged communication method, system and medium

Abstract

The application discloses a kind of load management terminal safe and reliable fusion communication method, and disclosed with the system of load management terminal safe and reliable fusion communication method, wherein load management terminal safe and reliable fusion communication method is converted into feature gene by the intrusion detection data set, and immune cell is generated by gene, the diversity of feature information is improved by cloning variation, to match abnormal data to prevent the possibility of intruder intrusion, also provide synergistic stimulation, further improve the accuracy of system.In addition, adaptive authentication mechanism is also introduced between terminal and main station, through the evaluation of context data, adaptive access authentication strategy arrangement is carried out, and time stamp, digital signature and NTRU encryption system are introduced in communication process, can cope with replay attack, verify the integrity of data, identity authentication and anti-denial, and have the ability of anti-quantum, face mass load management terminal, realize efficient and safe access communication strategy.

Description

Technical Field

[0001] This invention relates to the field of security protection for novel power system load management terminals, and particularly to a secure and reliable converged communication method and system for load management terminals. Background Technology

[0002] With the development and increasing intelligence of power management systems, the threats of cyberattacks they face are also gradually increasing, making the need for secure and reliable communication of load management terminals increasingly urgent. To meet this need, the security protection technology proposed in this invention utilizes techniques such as terminal-inherent security immunity, adaptive authentication strategy orchestration, and protocol security hardening to achieve terminal security protection and enhanced local communication security. This constructs a comprehensive security protection system compatible with existing security mechanisms, enabling a unified and coordinated response to the secure communication needs of different terminals and environments, thereby improving the overall security of the power system.

[0003] (1) Terminal Security Protection Technology Based on Immune Theory: The immune system of an organism possesses a high degree of autonomy, adaptability, and robustness. To ensure the security of the terminal itself, this invention studies terminal security protection technology based on immune theory. Immune theory refers to applying the principles and mechanisms of the biological immune system to the field of computer security to achieve endogenous security immunity of the terminal. Through this technology, the terminal can identify and respond to various security threats, including viruses, malware, and unknown attack methods. The application of immune theory enables the terminal to possess self-protection and self-repair capabilities, improving the security of the terminal itself.

[0004] (2) Terminal Security Access Technology Based on Adaptive Orchestration of Authentication Policies: To ensure the security of the terminal access process, this invention studies a terminal security access technology based on adaptive orchestration of authentication policies. The main objective of this technology is to dynamically configure and adjust the authentication policy according to the characteristics of the device and the requirements of the network environment when a terminal device accesses the network, ensuring that only legitimate and secure devices can access the network and providing appropriate permissions and service access control. It can perform fine-grained authentication and authorization based on information such as the terminal device's attributes, operating system, security configuration, and software version, combined with the security policy requirements of the network environment. This ensures that only legitimate terminals can access the power system in different terminal access scenarios. In this way, the security and efficiency of the authentication process can be improved when dealing with a massive number of load management terminals, and the needs of different terminal access scenarios can be adapted. Summary of the Invention

[0005] This invention aims to address at least one of the technical problems existing in the prior art. To this end, this invention proposes a secure and reliable converged communication method for load management terminals. This method leverages breakthroughs in security protection technologies for load management terminals in three aspects: the terminal itself, the access process, and network communication. It forms a comprehensive security protection system that is effectively compatible with existing security mechanisms, thereby supporting secure and reliable communication for massive load management terminals in new power systems.

[0006] The present invention also proposes a system with the above-mentioned method for selecting the controllability ratio of a controllable surge arrester under the aforementioned limited conditions.

[0007] The secure and reliable converged communication method for a load management terminal according to a first aspect of the present invention is characterized by comprising the following steps:

[0008] Load and run an immune-based terminal security protection model on the load management terminal;

[0009] The load management terminal sends a connection request to the master station, and the request message includes the load management terminal's own data.

[0010] The master station establishes a connection with the load management terminal, obtains the communication data sent by the load management terminal, and checks whether the master station retains the context data of the terminal. If it does, the master station authenticates the context data; otherwise, the authentication fails.

[0011] The load management terminal obtains communication data sent by the master station and checks whether the load management terminal retains its context data. If it does, it authenticates the context data; otherwise, the authentication fails.

[0012] If both the load management terminal and the main station are successfully authenticated, then access will be granted;

[0013] After successful access, the main station and the load management terminal respectively hash the communication data they have acquired, generate a digital signature, and take a timestamp. They then encrypt the communication data and send it to each other.

[0014] The load management terminal and the main station respectively acquire and decrypt the communication data, extract the digest of the decrypted original data, compare it, and verify the legality of the timestamp. If both the digest and the timestamp are authenticated, the data is considered secure; otherwise, the communication data is considered to have been tampered with.

[0015] The secure and reliable converged communication method for load management terminals according to embodiments of the present invention has at least the following beneficial effects: the embodiments of the present invention provide a breakthrough in the security protection technology of load management terminal body, access process and network communication, forming a comprehensive security protection system that is effectively compatible with existing security protection mechanisms, and supporting secure and reliable communication of massive load management terminals under the new power system.

[0016] According to some embodiments of the present invention, in the step of loading and running the terminal security protection model based on the immune theory on the load management terminal, the operation process of the security protection model includes:

[0017] Import abnormal data genes.

[0018] Through negative selection, clonal selection, and high-frequency mutation mechanisms, immune cells learn abnormal data characteristics and attack patterns, generating high-affinity memory cells.

[0019] The input data is presented with antigens, and features are extracted from the input data to obtain the characteristics of the antigens. The results are then input into a well-learned system, where a memory cell with the highest affinity votes to determine the test results.

[0020] Based on the test results, select whether to load the emergency response and event logging program for immune defense.

[0021] According to some embodiments of the present invention, the step of selecting whether to load the emergency response and event recording procedure for immune defense based on the detection results specifically includes:

[0022] The equipment safety administrator determines whether the data is abnormal. If so, proceed to the next step; otherwise, it is a false alarm of immune cells, and the immune cell is transferred to the immature immune cell population.

[0023] Perform security classification on abnormal data, determine whether immediate processing is required based on the security level, and perform disaster recovery backup. If necessary, proceed to the next step; otherwise, log and continue running the program.

[0024] Determine the type of anomaly that occurred, and check if the data is necessary. If not, discard the data; if so, proceed to the next step.

[0025] Check whether a memory has been formed from all previously encountered antigens and whether timely countermeasures are taken upon repeated exposure. If so, log the information and continue running; otherwise, proceed to the next step.

[0026] Perform rapid reconstruction of the system operating environment and restore the previous state;

[0027] The generated emergency response strategy will be recorded and the results will be fed back.

[0028] According to some embodiments of the present invention, the process of authenticating the context data includes:

[0029] Import the pre-defined authentication security scoring strategy model standard template library into the main site;

[0030] The master station sends a data request message through the management terminal. When the master station receives a connection request from the terminal, it will negotiate the access with the terminal. The negotiation will obtain context data, and then the master station will collect the historical data of the previous connections of the site.

[0031] Adaptive authentication calculates the risk associated with authentication attempts based on factors established during user type and system settings.

[0032] If the risk is below a preset first security threshold, the authentication attempt is allowed; if the risk is between the first and second security thresholds, the user is required to provide other authentication methods; if the risk is above the second security threshold, the authentication attempt will be rejected, the attacker will be blocked, or the authentication attempt will be redirected to a secure zone.

[0033] According to some embodiments of the present invention, the steps of the information receiver acquiring and decrypting the communication data, extracting the digest of the decrypted original data, comparing it, and verifying the legality of the timestamp specifically include:

[0034] A timestamp is generated for each communication message, and a digital signature is generated by hashing the data and timestamp. The communication data in the smart grid is encrypted using the NTRU encryption system. After encryption, the total length is appended to the message header, and then the message data is sent to the receiver.

[0035] After receiving the message, the master station obtains the encrypted communication data, timestamp, and digital signature, decrypts it, and determines the validity of the timestamp. If the timestamp is invalid, the communication data is discarded; if it is valid, the integrity is verified.

[0036] Integrity verification is performed by calculating a message digest from the decrypted communication data and timestamp. The digital signature is decrypted using the trusted cryptographic module and the peer certificate obtained during node identity authentication. The decryption is then compared with the calculated message digest. If they are different, the communication data is discarded; if they are the same, the timestamp is removed to obtain the plaintext protocol data.

[0037] A secure and reliable converged communication system for load management terminals according to a second aspect embodiment of the present invention is characterized in that it comprises:

[0038] The security immunity module is capable of loading and running an immunity-based terminal security protection model on the load management terminal;

[0039] The connection request module, located in the load management terminal, can send connection requests to the main station. The request message includes data from the load management terminal itself.

[0040] The main station verification module, located in the main station, can receive communication data sent by the load management terminal and verify whether the main station retains the context data of the terminal. It performs adaptive authentication on the communication data. If the context data exists, it authenticates the context data; otherwise, the authentication fails.

[0041] The terminal verification module is set in the load management terminal. It can receive communication data sent by the master station and verify whether the load management terminal retains the context data of the load management terminal. It performs adaptive authentication on the communication data. If the context data is present, it will be authenticated. If not, the authentication will fail.

[0042] If the authentication verification module confirms that both the load management terminal and the master station are successfully authenticated, then the access process will proceed.

[0043] The encryption module enables the main station and the load management terminal to hash their respective acquired communication data, generate digital signatures, and timestamp the data after successful access. The encrypted communication data is then sent to the other party.

[0044] The verification module, load management terminal, and main station respectively acquire and decrypt the communication data, extract the digest of the decrypted original data, compare it, and verify the legality of the timestamp. If both the digest and the timestamp are authenticated, the data is considered secure; otherwise, the communication data is considered to have been tampered with.

[0045] According to some embodiments of the present invention, the operation process of the security protection model in the security immunity module includes:

[0046] Import abnormal data genes;

[0047] Through negative selection, clonal selection, and high-frequency mutation mechanisms, immune cells learn abnormal data characteristics and attack patterns, generating high-affinity memory cells.

[0048] The input data is presented with antigens, and features are extracted from the input data to obtain the characteristics of the antigens. The results are then input into a well-learned system, where a memory cell with the highest affinity votes to determine the test results.

[0049] Based on the test results, select whether to load the emergency response and event logging program for immune defense.

[0050] According to some embodiments of the present invention, the step of selecting whether to load the emergency response and event recording procedure for immune defense based on the detection results specifically includes:

[0051] The equipment safety administrator determines whether the data is abnormal. If so, proceed to the next step; otherwise, it is a false alarm of immune cells, and the immune cell is transferred to the immature immune cell population.

[0052] Perform security classification on abnormal data, determine whether immediate processing is required based on the security level, and perform disaster recovery backup. If necessary, proceed to the next step; otherwise, log and continue running the program.

[0053] Determine the type of anomaly that occurred, and check if the data is necessary. If not, discard the data; if so, proceed to the next step.

[0054] Check whether a memory has been formed from all previously encountered antigens and whether timely countermeasures are taken upon repeated exposure. If so, log the information and continue running; otherwise, proceed to the next step.

[0055] Perform rapid reconstruction of the system operating environment and restore the previous state;

[0056] The generated emergency response strategy will be recorded and the results will be fed back.

[0057] According to some embodiments of the present invention, the process of authenticating the context data in the main station verification module and the terminal verification module includes:

[0058] Import the pre-defined authentication security scoring strategy model standard template library into the main site;

[0059] The load management terminal sends a data request message. When the master station receives a connection request from the terminal, it will conduct access negotiation with the terminal. The negotiation will obtain context data, and then the master station will collect historical data of the previous connections of the site.

[0060] Adaptive authentication calculates the risk associated with authentication attempts based on factors established during user type and system settings.

[0061] If the risk is below a preset first security threshold, the authentication attempt is allowed; if the risk is between the first and second security thresholds, the user is required to provide other authentication methods; if the risk is above the second security threshold, the authentication attempt will be rejected, the attacker will be blocked, or the authentication attempt will be redirected to a secure zone.

[0062] According to some embodiments of the present invention, the verification module includes:

[0063] The encryption element can generate a timestamp for each communication message and generate a digital signature by hashing the data and timestamp. The NTRU encryption system is used to encrypt the communication data in the smart grid. After encryption, the total length is appended to the message header, and then the message data is sent to the receiver.

[0064] The validity verification element involves the master station receiving a message, obtaining the encrypted communication data, timestamp, and digital signature, decrypting it, and determining the validity of the timestamp. If the timestamp is invalid, the communication data is discarded; if it is valid, the integrity is verified.

[0065] The integrity verification element is capable of performing integrity verification. It calculates a message digest from the decrypted communication data and timestamp, decrypts the digital signature using the trusted cryptographic module and the peer certificate obtained during the node identity authentication process, and compares it with the calculated message digest. If they are different, the communication data is discarded; if they are the same, the timestamp is removed and plaintext protocol data is obtained.

[0066] An embodiment of the third aspect of the present invention provides a computer-readable storage medium storing computer-executable instructions for performing the above-described secure and reliable converged communication method for a load management terminal.

[0067] Additional aspects and advantages of the invention will be set forth in part in the description which follows, and in part will be obvious from the description, or may be learned by practice of the invention. Attached Figure Description

[0068] The above and / or additional aspects and advantages of the present invention will become apparent and readily understood from the description of the embodiments taken in conjunction with the following drawings, in which:

[0069] Figure 1 This is a schematic diagram illustrating the steps of the secure and reliable converged communication method for load management terminals according to an embodiment of the present invention;

[0070] Figure 2 This is a structural block diagram of a secure and reliable converged communication system for load management terminals according to an embodiment of the present invention. Detailed Implementation

[0071] Embodiments of the present invention are described in detail below. Examples of these embodiments are shown in the accompanying drawings, wherein the same or similar reference numerals denote the same or similar elements or elements having the same or similar functions throughout. The embodiments described below with reference to the accompanying drawings are exemplary and are only used to explain the present invention, and should not be construed as limiting the present invention.

[0072] In the description of this invention, it should be understood that the orientation descriptions, such as up, down, front, back, left, right, etc., are based on the orientation or positional relationship shown in the accompanying drawings. They are only for the convenience of describing this invention and simplifying the description, and do not indicate or imply that the device or element referred to must have a specific orientation, or be constructed and operated in a specific orientation. Therefore, they should not be construed as limiting this invention.

[0073] In the description of this invention, "several" means one or more, "more than" means two or more, "greater than," "less than," and "exceeding" are understood to exclude the stated number, while "above," "below," and "within" are understood to include the stated number. The use of "first" and "second" in the description is merely for distinguishing technical features and should not be construed as indicating or implying relative importance, or implicitly indicating the number of indicated technical features, or implicitly indicating the order of the indicated technical features.

[0074] In the description of this invention, unless otherwise explicitly defined, terms such as "set up," "install," and "connect" should be interpreted broadly, and those skilled in the art can reasonably determine the specific meaning of the above terms in this invention in conjunction with the specific content of the technical solution.

[0075] Reference Figure 1 The embodiments of the present invention provide a secure and reliable converged communication method based on immune theory and authentication strategy adaptive orchestration, which includes the following steps:

[0076] Step S100: Load and run the terminal security protection model based on the immune theory on the load management terminal.

[0077] The purpose is to achieve intrinsic security immunity on the terminal and ensure the security of the terminal itself.

[0078] Step S200: The load management terminal sends a connection request to the master station. The request message includes the load management terminal's own data.

[0079] Step S300: The master station establishes a connection with the load management terminal, obtains the communication data sent by the load management terminal, and checks whether the master station retains the context data of the terminal. If it does, the master station authenticates the context data; otherwise, the authentication fails.

[0080] Step S400: The load management terminal obtains the communication data sent by the master station and checks whether the load management terminal retains the context data of the load management terminal. If it does, the context data is authenticated; otherwise, the authentication fails.

[0081] Step S500: If the authentication of both the load management terminal and the master station is successful, then access is performed.

[0082] Step S600: After successful access, hash the communication data, generate a digital signature, and obtain a timestamp. Then, encrypt the communication data and send it to the other party.

[0083] Step S700: The information receiver obtains and decrypts the communication data, extracts the digest of the decrypted original data, compares it, and verifies the legality of the timestamp. If both the digest and the timestamp are authenticated, the data is considered secure; otherwise, the communication data is considered to have been tampered with.

[0084] Specifically, step S100 above includes:

[0085] Step S110: Import abnormal data genes.

[0086] An immune endogenous protection system is embedded in the power load management terminal. An abnormal gene library is initially established, and the initial management personnel input abnormal data to establish an antibody gene library: Agd = Agd1∪Agd2∪…∪Agd n .

[0087] The immune learning module learns features from abnormal data, and then obtains the feature representation in the random detector (i.e., immune cells) in the form of an l-dimensional feature vector. In the formula It is an immune cell antibody gene, belonging to the Agd gene. k The antibody gene library is represented by the variable 'l', where 'l' represents the gene length. The inspector is presented as a quintuple. <d k ,sta,age,reccoun,macoun,aff>,where d k is the feature vector of the sample, which is the feature vector of l-tuples for random detectors; sta is the state bit, sta∈{0,1}, 0 represents immature, 1 represents mature; age is the survival time (ms); reccount is the recognition counter; mecount is the matching counter in the memory state; aff is the affinity of immune cells.

[0088] Step S120: Through negative selection, clonal selection and high-frequency mutation mechanisms, immune cells learn abnormal data characteristics and attack patterns, generating memory cells with high affinity.

[0089] Let the affinity function be f aft (b k ):

[0090]

[0091] Among them, immune cells b k ∈B k immune cells b k Affinity is for B cells in the same group of immune cells k The mean cosine value is used to represent the immune cells of the same type. The larger the mean cosine value, the stronger the ability to represent the immune cells of that type, and the stronger the ability to detect abnormalities or attacks. However, to avoid false positives in immune cell detection, it is necessary to subtract the false positive portion from the average similarity of immune cells of the same type. The false positive portion is represented by a penalty function.

[0092]

[0093] In the formula, m represents the immune cell b. kOther immune cells X i ∈B i The number of immune cells whose cosine value (i≠k) is greater than the similarity threshold ω; where cos(x) i ,y i ) for immune cells x i and y j Cosine similarity of the weights of each gene.

[0094] Specifically, first, a set Self is given, denoted as the self set; candidate detectors (i.e., immature immune cells B) are randomly generated, with the state sta set to 0, and are added to the candidate detector set; the affinity between the candidate detector set and each element in the self set is calculated one by one, and it is determined whether the matching condition is met.

[0095] If the sum of affinities exceeds the threshold, the detector is identified as self and deleted; if the sum of affinities does not exceed the threshold, it is identified as a non-self element and placed into a qualified set of random detectors (i.e., mature immune cells R), and the detector's state sta is set to 1.

[0096] Mature immune cells will match with the antigen. If a match is successful, the count is incremented by 1. When the count > 2, the detector is activated, and mature immune cells are cloned. The number of clones is proportional to the affinity of the detector, i.e., C_num(x k )=γf aff (x k ), where γ is the cloning coefficient, set to 5, and the cloned immune cells are mutated with a mutation probability of 1-f. aff (x k The selection is made using a roulette wheel.

[0097] The mutation process is Gaussian mutation, meaning that for the individual x affected by the clonal mutation operator... i Quantity:

[0098] x i (j),i=1,2,…,n,j=1,2…,m (3)

[0099] η′ i (j)=η i (j)exp(τ′N(0,1)+τN i (0, 1)) (4)

[0100] x i ′(j)=x i (j)+η i ′(j)N(0,1) (5)

[0101] Where x i (j),xi ′(j),η i (j),η i ′(j) represent vector x i x i ′,η i η i The j-th component of ′, N i (0,1) represents the normally distributed random number generated for each j, and N(0,1) is a normally distributed random variable with a mean of 0 and a variance of 1. The parameters τ and τ′ are taken as follows: and

[0102] The mutated immune cell set is added to the immature immune cell set B. If it is activated (reccount>2), it is added to the mature immune cell set R. From set R, the m mature immune cells with the highest affinity are selected to form the next generation of mature immune cell set R′, so as to ensure that the low affinity antibodies in the population are replaced, thereby maintaining antibody diversity.

[0103] Next, add immune cells from immune cell set B with an affinity greater than the memory cell affinity threshold δ1 to memory cell set M. The memory cell affinity threshold δ1 is set to 0.5. When a memory cell successfully matches an antigen, the memory cell count is incremented by 1. Repeat the above process until the average affinity reaches a certain threshold θ, at which point the update ends. The threshold θ is set to 0.75.

[0104] Step S130: The input data is presented with antigen, and features are extracted from the input data to obtain the characteristics of the antigen. The antigen is then input into the learned system, and the test result is determined by a memory cell with the highest affinity.

[0105] The detection module presents the input data using antigens, which involves feature extraction. These features are categorized into retained features and user-defined features, with a focus on retaining the retained features during antigen presentation. The presented data is then input into the trained system. The detection result is determined by a vote of ρ memory cells with the highest affinity, where ρ is set to 5. The principle behind memory cells determining whether data is abnormal is the matching between the data to be detected and the memory cells. This matching process requires calculating cosine similarity.

[0106]

[0107] in These are the weights of the h-th gene in the memory cell. If the similarity exceeds the threshold δ2, the inspector will determine it as abnormal or attack data and delete the data. The threshold δ2 is set to 0.5.

[0108] Step S140: Based on the test results, select whether to load the emergency response and event recording program for immune defense.

[0109] If the antigen successfully matches with an immune cell, an external co-stimulation mechanism is triggered, and abnormal data is retained in a safety buffer and then reported to the device administrator for further evaluation. Specifically, this includes:

[0110] Step S141: The equipment safety administrator determines whether the data is abnormal. If so, proceed to the next step; otherwise, it is a false alarm of immune cells, and the immune cells are transferred to the immature immune cell population.

[0111] Step S142: Classify the abnormal data for security, determine whether immediate processing is required based on the security level, and perform disaster recovery backup. If necessary, proceed to the next step; otherwise, record the log and continue running the program.

[0112] Step S143: Determine the type of the anomaly and check if the data is necessary. If not, discard the data; if so, proceed to the next step.

[0113] Step S144: Check whether memory has been formed through all previously encountered antigens and whether timely countermeasures have been taken upon repeated exposure. If yes, log the process and continue. If not, proceed to the next step.

[0114] Step S145: Perform rapid reconstruction of the system operating environment and restore the system to its previous state, i.e., disaster recovery. This mainly uses disaster recovery backup, data mirroring, snapshots and other technologies to avoid the escalation of threat attacks.

[0115] Step S146: Generate the emergency response strategy and record the processing results.

[0116] Furthermore, step S300 specifically includes:

[0117] Step S310: Import the preset authentication security scoring strategy model standard template library into the main site.

[0118] When the load management terminal connects to the master station, the preset authentication security scoring strategy model standard template library is imported into both the master station and the terminal. Data request messages are sent through the management terminal. When the master station receives a connection request from the terminal, it enters access negotiation. Through negotiation, some historical data is obtained, including site behavior data, attack threat data, threat intelligence data, and management behavior data.

[0119] Step S320: Send a data request message through the management terminal. When the master station receives a connection request from the terminal, it will conduct access negotiation with the terminal. Context data will be obtained through the negotiation, and then the master station will collect historical data of the previous connections of the site.

[0120] Specifically, the context data symbols involved in the model are defined as follows: x = (x1, x2, ..., x...) d ), representing a set of d-dimensional context feature vectors when connecting to a certain site. All features will be preprocessed by multi-driver source data and then transferred to the trust assessment center according to the specified data format.

[0121] Given a set of context feature vectors x, where U represents the identity of the device currently in use, and L and I represent whether the user is a legitimate user or an illegitimate user, respectively. X and U are random variables of x and u, respectively. For the two categories of legitimate and illegitimate users, the following condition must be met: When X = x, U = L; otherwise, U = 1. That is, p(X = x | U = L) represents the security level of a legitimate site in the current context. The larger (X = x | U = L) is, the safer the environment is for legitimate users, i.e., the higher the security level; conversely, the smaller the p(X = x | U = L) is, the lower the security level.

[0122] Furthermore, when all contextual features are independent, Then, the probability distribution of the user under a single contextual feature is calculated.

[0123] Step S330: Adaptive authentication calculates the risk associated with the authentication attempt based on factors established during user type and system settings.

[0124] After determining the security level of the context, it is also necessary to consider the information protection level of the proposed access sites. The quantitative scoring mechanism for this protection level is determined by the actual situation. Sites that users deem important should use stronger authentication methods, and vice versa. To consider both cases, the evaluation model designed in this invention is as follows: f(x,v)=(P v ×v)+(P x ×x). Where v refers to the importance of the user to the site, x refers to the security level of the site, and P v P represents the weight of importance. x Weights are assigned to the level of security. A set of security thresholds θ0 and θ1 are defined.

[0125] Step S340: If the risk is low enough, the authentication attempt can be allowed without additional authentication steps; if the risk is moderate, the workflow can be escalated and the user can be required to provide other authentication methods. After this step, the user will be approved, but the attacker will be stopped; if the risk is too high, the authentication attempt will be rejected, the attacker will be blocked, or the authentication attempt can be redirected to a secure area for further observation.

[0126] f(x,v) is the score after comprehensively considering the two situations described above. Based on this score, the system adaptively selects different strengths of continuous authentication methods: if the score of f(x,v) is high (exceeding the security threshold θ1), it indicates that the user's current environment has a high security level or the site data is not very important, so no additional authentication steps are required to allow the authentication attempt; if the risk is moderate (exceeding the security threshold θ0 but less than the security threshold θ1), the workflow can be escalated and the user can be required to provide other authentication methods; if the risk is too high, the authentication attempt will be rejected, the attacker will be blocked, or the authentication attempt can be redirected to a safe zone for further observation.

[0127] Furthermore, other authentication methods (one-time passwords) are characterized in that each master station and terminal has an associated token generator or authentication application. During the authentication process, the remote master station sends a random challenge to the terminal, which uses the token generator to generate a one-time password and sends it back to the remote host for verification. If the verification fails, an exception handling prompt is issued.

[0128] For step S400, similar to step S300 above, adaptive authentication of the load management terminal to the master station is implemented.

[0129] Furthermore, in order to enhance local communication security through data security encryption technology and data integrity protection technology, step S700 above includes:

[0130] Step S710: Generate a timestamp for each communication message and generate a digital signature by hashing the data and timestamp. Use the NTRU encryption system to encrypt the communication data in the smart grid. After encryption, append the total length to the message header and then send the message data to the receiver.

[0131] Step S720: After receiving the message, the master station obtains the encrypted communication data, timestamp and digital signature, decrypts it, and judges the validity of the timestamp. If it is invalid, the communication data is discarded; if it is valid, the integrity is verified.

[0132] Step S730: Perform integrity verification. Calculate a message digest for the decrypted communication data and timestamp. Decrypt the digital signature using the trusted cryptographic module and the counterparty certificate obtained during node identity authentication. Compare the decrypted digital signature with the calculated message digest. If they are different, discard the communication data. If they are the same, remove the timestamp and obtain the plaintext protocol data.

[0133] Following the steps outlined above, a secure and reliable converged communication method based on immune theory and adaptive orchestration of authentication strategies provides a breakthrough in security protection technologies across the load management terminal itself, the access process, and network communication. This forms a comprehensive security protection system effectively compatible with existing security mechanisms, supporting secure and reliable communication for massive load management terminals in new power systems. However, the construction of the system's immune system and adaptive strategies still needs to be determined based on actual requirements.

[0134] In summary, the key to this application lies in establishing a protection model based on immune theory on the load management terminal and introducing a synergistic stimulation mechanism, which consists of a gene generation module, an immune learning module, a detection module, and an emergency response module. The characteristic representation of immune cells in this model is an l-dimensional feature vector. The checker is represented as a 5-tuple. <d k ,sta,age,reccoun,macoun,aff>,its dynamic evolution process is described as follows Based on the affinity function: The false positive portion is represented by a penalty function: This is to facilitate the renewal and clonal mutation of immune cells.

[0135] First, candidate detectors (i.e., immature immune cells B) are randomly generated from the existing feature vectors, with the state sta set to 0, and added to the candidate detector set. Affinity is calculated for each element in the candidate detector set and the self-generated set. If the sum of affinity values ​​exceeds a threshold of 0.5, the detector is considered self-generated and deleted. If the sum of affinity values ​​does not exceed the threshold, the element is considered non-self-generated and added to the qualified random detector set (i.e., mature immune cells R), with the detector's state sta set to 1. Mature immune cells will match with the antigen. If a match is successful, reccoun is incremented by 1. When reccoun > 2, the detector is activated, and mature immune cells are cloned. The number of clones is proportional to the detector's affinity, i.e., C_num(x k )=γf aff (x k ), where γ is the cloning coefficient, set to 5, and the cloned immune cells are mutated with a mutation probability of 1-f. aff (x kThe selection process uses a roulette wheel approach, with Gaussian mutation as the mutation process. The mutated immune cell set is added to the immature immune cell set B. If activated (reccount>2), it is added to the mature immune cell set R. From set R, the m most affinity-rich mature immune cells are selected to form the next generation mature immune cell set R′. Immune cells from immune cell set B with affinity greater than the memory cell affinity threshold δ1 are added to the memory cell set M. The memory cell affinity threshold δ1 is set to 0.5. When a memory cell successfully matches the antigen, mecoun is incremented by 1. This process is repeated until the average affinity reaches a certain threshold θ, at which point the update ends. The threshold θ is set to 0.75. The detection module extracts features from the input data and inputs the extracted data into the learned system. The detection result is determined by the vote of the ρ memory cells with the highest affinity, where ρ is set to 5. The principle behind memory cells determining whether data is abnormal is the matching between the data to be detected and the memory cells. The matching process requires calculating cosine similarity.

[0136]

[0137] in These represent the weights of the h-th gene in the memory cell. If the similarity exceeds a threshold δ2, the checker classifies it as abnormal or malicious data and deletes it. The threshold δ2 is set to 0.5. If the antigen successfully matches the immune cell, an external co-stimulation mechanism is triggered, and the abnormal data is stored in a security buffer and reported to the device administrator for further evaluation.

[0138] In summary, the key to this application lies in establishing an adaptive authentication mechanism for the load management terminal during the access process between sites. The context data symbols involved in the model are defined as follows: x = (x1, x2, ..., x d ), representing a set of d-dimensional context feature vectors when connecting to a certain site. When all context features are independent, Then, the probability distribution of the user under a single contextual feature is calculated. This is achieved by evaluating the function f(x,v)=(P). v ×v)+(P x

[0139] ×x) assesses access security based on contextual information and site importance, then orchestrates adaptive authentication policies. A high score for f(x,v) (exceeding the security threshold θ1) indicates a high level of security in the user's current environment or that the site data is not critical, allowing authentication attempts without additional authentication steps. If the risk is moderate (exceeding the security threshold θ0 but less than the security threshold θ1), the workflow can be escalated to require the user to provide alternative authentication methods, such as one-time passwords. If the risk is too high, authentication attempts will be rejected, attackers will be blocked, or authentication attempts can be redirected to a secure area for further observation.

[0140] In summary, the key to this application lies in the communication process between stations. Before data transmission, a timestamp is taken, the data is hashed, and a digital signature is generated. The NTRU encryption system is used to encrypt the communication data in the smart grid. After encryption, the total length is appended to the message header, and then the message data is sent to the receiver. Upon receiving the message, the receiver obtains the encrypted communication data, timestamp, and digital signature, decrypts them, and determines the validity of the timestamp. If the timestamp is invalid, the communication data is discarded; if valid, integrity verification is performed. A message digest is calculated from the decrypted communication data and timestamp. The digital signature is decrypted using the cryptographic module and the counterparty's certificate obtained during node authentication. The signature is compared with the calculated message digest. If they differ, the communication data is discarded; if they match, the timestamp is removed, and the plaintext protocol data is obtained.

[0141] As can be seen from the above embodiments, this method mainly transforms the intrusion detection dataset into feature genes, generates immune cells from these genes, and enhances the diversity of feature information through cloning and mutation. This allows it to match abnormal data to prevent attackers from intruding and provides co-stimulation, further improving the system's accuracy. Furthermore, an adaptive authentication mechanism is introduced between the terminal and the master station. By evaluating contextual data, an adaptive access authentication strategy is orchestrated, and timestamps, digital signatures, and NTRU encryption are introduced into the communication process. This enables the system to cope with replay attacks, verify data integrity, authentication, and non-repudiation, and possesses quantum resistance capabilities. Facing a massive number of load management terminals, this method achieves an efficient and secure access communication strategy. Clearly, this method, based on immune principles and adaptive authentication for load management terminal security protection, effectively addresses existing challenges.

[0142] Another aspect of this application provides a secure and reliable converged communication system for load management terminals, such as... Figure 2 As shown, the system 20 includes: a security immunity module 201, a link request module 202, a main station verification module 203, a terminal verification module 204, an authentication verification module 205, an encryption module 206, and a verification module 207.

[0143] Security Immunity Module 201 is capable of loading and running an immunity-based terminal security protection model on the load management terminal;

[0144] The connection request module 202 is set in the load management terminal and can send a connection request to the master station. The request message includes the load management terminal's own data.

[0145] The main station verification module 203 is set in the main station and can receive communication data sent by the load management terminal and verify whether the main station retains the context data of the terminal. It performs adaptive authentication on the communication data.

[0146] The terminal verification module 204 is installed in the load management terminal. It can receive communication data sent from the master station and verify whether the load management terminal retains the context data of the load management terminal. It performs adaptive authentication on the communication data.

[0147] The authentication verification module 205 will initiate access if both the load management terminal and the master station are successfully authenticated.

[0148] The encryption module 206 is capable of hashing the communication data, generating a digital signature, and taking a timestamp. The communication data is then encrypted using the NTRU encryption system and sent to the other party.

[0149] Verification module 207: The information receiver obtains the communication data and decrypts it, extracts the digest of the decrypted original data, compares it, and verifies the legality of the timestamp. If they match, the data is considered secure; otherwise, the communication data is considered to have been tampered with.

[0150] This application's embodiments transform intrusion detection datasets into feature genes, generate immune cells from these genes, and enhance the diversity of feature information through cloning and mutation. This allows for matching abnormal data to the likelihood of preventing attacker intrusion and provides synergistic stimulation, further improving the system's accuracy. Furthermore, an adaptive authentication mechanism is introduced between the terminal and the master station. By evaluating contextual data, adaptive access authentication strategies are orchestrated, and timestamps, digital signatures, and NTRU encryption are incorporated into the communication process. This enables the system to withstand replay attacks, verify data integrity, authenticate identities, and provide non-repudiation, while also possessing quantum resistance capabilities. This achieves an efficient and secure access communication strategy for managing massive loads of terminals.

[0151] Furthermore, the operation process of the security protection model in the security immunity module includes:

[0152] Import abnormal data genes.

[0153] Through negative selection, clonal selection, and high-frequency mutation mechanisms, immune cells learn abnormal data characteristics and attack patterns, generating high-affinity memory cells.

[0154] The input data is presented with antigens, and features are extracted from the input data to obtain the characteristics of the antigens. The results are then input into a well-learned system, where a memory cell with the highest affinity votes to determine the test results.

[0155] Based on the test results, select whether to load the emergency response and event logging program for immune defense.

[0156] Furthermore, based on the test results, the step of selecting whether to load the emergency response and event logging procedures for immune defense specifically includes:

[0157] The equipment safety administrator determines whether the data is abnormal. If so, proceed to the next step; otherwise, it is a false alarm of immune cells, and the immune cell is transferred to the immature immune cell population.

[0158] Perform security classification on abnormal data, determine whether immediate processing is required based on the security level, and perform disaster recovery backup. If necessary, proceed to the next step; otherwise, log and continue running the program.

[0159] Determine the type of anomaly that occurred, and check if the data is necessary. If not, discard the data; if so, proceed to the next step.

[0160] Check whether a memory has been formed from all previously encountered antigens and whether timely countermeasures are taken upon repeated exposure. If so, log the information and continue running; otherwise, proceed to the next step.

[0161] Rapid reconstruction of the system operating environment and restoration to the previous state, i.e. disaster recovery, are carried out, mainly using disaster recovery backup, data mirroring, snapshot and other technologies to avoid the expansion of threat attacks;

[0162] The generated emergency response strategy will be recorded and the results will be fed back.

[0163] Furthermore, the adaptive authentication process in the main site verification module and the terminal verification module includes:

[0164] Import the pre-defined authentication security scoring strategy model standard template library into the main site;

[0165] The master station sends a data request message through the management terminal. When the master station receives a connection request from the terminal, it will negotiate the access with the terminal. The negotiation will obtain context data, and then the master station will collect the historical data of the previous connections of the site.

[0166] Adaptive authentication calculates the risk associated with authentication attempts based on factors established during user type and system settings.

[0167] If the risk is low enough, authentication attempts can be allowed without additional authentication steps; if the risk is moderate, the workflow can be escalated to require the user to provide alternative authentication methods. After this step, the user will be approved, but the attacker will be stopped; if the risk is too high, authentication attempts will be rejected, the attacker will be blocked, or the authentication attempts can be redirected to a secure area for further observation.

[0168] Furthermore, the verification module includes:

[0169] The encryption element can generate a timestamp for each communication message and generate a digital signature by hashing the data and timestamp. The NTRU encryption system is used to encrypt the communication data in the smart grid. After encryption, the total length is appended to the message header, and then the message data is sent to the receiver.

[0170] The validity verification element involves the master station receiving a message, obtaining the encrypted communication data, timestamp, and digital signature, decrypting it, and determining the validity of the timestamp. If the timestamp is invalid, the communication data is discarded; if it is valid, the integrity is verified.

[0171] The integrity verification element is capable of performing integrity verification. It calculates a message digest from the decrypted communication data and timestamp, decrypts the digital signature using the trusted cryptographic module and the counterparty certificate obtained during the node identity authentication process, and compares it with the calculated message digest. If they are different, the communication data is discarded; if they are the same, the timestamp is removed and plaintext protocol data is obtained.

[0172] The device embodiments described above are merely illustrative. The units described as separate components may or may not be physically separate; that is, they may be located in one place or distributed across multiple network units. Some or all of the modules can be selected to achieve the purpose of this embodiment according to actual needs.

[0173] It will be understood by those skilled in the art that all or some of the steps and systems in the methods disclosed above can be implemented as software, firmware, hardware, and suitable combinations thereof. Some or all of the physical components can be implemented as software executed by a processor, such as a central processing unit, digital signal processor, or microprocessor, or as hardware, or as an integrated circuit, such as an application-specific integrated circuit. Such software can be distributed on a computer-readable medium, which can include computer storage media (or non-transitory media) and communication media (or transient media). As is known to those skilled in the art, the term computer storage media includes volatile and non-volatile, removable and non-removable media implemented in any method or technology for storing information (such as computer-readable instructions, data structures, program modules, or other data). Computer storage media includes, but is not limited to, RAM, ROM, EEPROM, flash memory or other memory technologies, CD-ROM, digital versatile disc (DVD) or other optical disc storage, magnetic cartridges, magnetic tape, disk storage or other magnetic storage devices, or any other medium that can be used to store desired information and is accessible to a computer. Furthermore, as is known to those skilled in the art, communication media typically contain computer-readable instructions, data structures, program modules, or other data in modulated data signals such as carrier waves or other transmission mechanisms, and may include any information delivery medium.

[0174] The above is a detailed description of the preferred embodiments of this application. However, this application is not limited to the above embodiments. Those skilled in the art can make various equivalent modifications or substitutions without departing from the spirit of this application. All such equivalent modifications or substitutions are included within the scope defined by the claims of this application.

Claims

1. A secure and reliable converged communication method for load management terminals, characterized in that, Includes the following steps: An immune-based terminal security protection model is loaded and run on the load management terminal. The model's operation includes: importing abnormal data genes; promoting immune cells to learn abnormal data characteristics and attack patterns through negative selection, clonal selection, and high-frequency mutation mechanisms, generating high-affinity memory cells; presenting input data to antigens, extracting features from the input data to obtain antigen characteristics, inputting these features into the learned system, and having several memory cells with the highest affinity vote to determine the detection result; and, based on the detection result, selecting whether to load emergency handling and event logging procedures for immune defense. The context data symbols involved in the model are defined as follows: , represents a set of d-dimensional context feature vectors when connecting to a certain site; All features will be preprocessed by multi-driver source data and then transferred to the trust assessment center in the specified data format. The load management terminal sends a connection request to the master station, and the request message includes the load management terminal's own data. The master station establishes a connection with the load management terminal, obtains the communication data sent by the load management terminal, and checks whether the master station retains the context data of the terminal. If it does, the context data is used for authentication; otherwise, the authentication fails. The load management terminal obtains communication data sent by the master station and checks whether the load management terminal retains its context data. If it does, it authenticates the context data; otherwise, the authentication fails. If both the load management terminal and the main station are successfully authenticated, then access will be granted; After successful access, the main station and the load management terminal respectively hash the communication data they have acquired, generate a digital signature, and take a timestamp. They then encrypt the communication data and send it to each other. The load management terminal and the main station respectively acquire and decrypt the communication data, extract the digest of the decrypted original data, compare it, and verify the legality of the timestamp. If both the digest and the timestamp are authenticated, the data is considered secure; otherwise, the communication data is considered to have been tampered with.

2. The method according to claim 1, characterized in that, The step of selecting whether to load the emergency response and event logging program for immune defense based on the test results specifically includes: The equipment safety administrator determines whether the data is abnormal. If so, proceed to the next step; otherwise, it is a false alarm of immune cells, and the immune cell is transferred to the immature immune cell population. Perform security classification on abnormal data, determine whether immediate processing is required based on the security level, and perform disaster recovery backup. If necessary, proceed to the next step; otherwise, log and continue running the program. Determine the type of anomaly that occurred, and check if the data is necessary. If not, discard the data; if so, proceed to the next step. Check whether a memory has been formed from all previously encountered antigens and whether timely countermeasures are taken upon repeated exposure. If so, log the information and continue running; otherwise, proceed to the next step. Perform rapid reconstruction of the system operating environment and restore the previous state; The generated emergency response strategy will be recorded and the results will be fed back.

3. The method according to claim 1, characterized in that, The process of authenticating the context data includes: Import the pre-defined authentication security scoring strategy model standard template library into the main site; The master station sends a data request message through the management terminal. When the master station receives a connection request from the terminal, it will negotiate the access with the terminal. The negotiation will obtain context data, and then the master station will collect the historical data of the previous connections of the site. Adaptive authentication calculates the risk associated with authentication attempts based on factors established during user type and system settings. If the risk is below a preset first security threshold, the authentication attempt is allowed; if the risk is between the first and second security thresholds, the user is required to provide other authentication methods; if the risk is above the second security threshold, the authentication attempt will be rejected, the attacker will be blocked, or the authentication attempt will be redirected to a secure zone.

4. The method according to claim 1, characterized in that, The steps of the load management terminal and the main station acquiring and decrypting the communication data, extracting the digest of the decrypted original data, comparing it, and verifying the legality of the timestamp specifically include: A timestamp is generated for each communication message, and a digital signature is generated by hashing the data and timestamp. The communication data in the smart grid is encrypted using the NTRU encryption system. After encryption, the total length is appended to the message header, and then the message data is sent to the receiver. After receiving the message, the master station obtains the encrypted communication data, timestamp, and digital signature, decrypts it, and determines the validity of the timestamp. If the timestamp is invalid, the communication data is discarded; if it is valid, the integrity is verified. Integrity verification is performed by calculating a message digest from the decrypted communication data and timestamp. The digital signature is decrypted using the trusted cryptographic module and the peer certificate obtained during node identity authentication. The decryption is then compared with the calculated message digest. If they are different, the communication data is discarded; if they are the same, the timestamp is removed to obtain the plaintext protocol data.

5. A secure and reliable converged communication system for load management terminals, characterized in that, include: The security immunity module is capable of loading and running an immunity-based terminal security protection model on the load management terminal; The security protection model operation process includes: importing abnormal data genes; promoting immune cells to learn abnormal data characteristics and attack patterns through negative selection, clonal selection, and high-frequency mutation mechanisms to generate high-affinity memory cells; presenting the input data with antigens, extracting features from the input data to obtain antigen characteristics, inputting them into the learned system, and having several memory cells with the highest affinity vote to determine the detection result; and selecting whether to load emergency processing and event recording procedures for immune defense based on the detection result. The context data symbols involved in the model are defined as follows: , represents a set of d-dimensional context feature vectors when connecting to a certain site; All features will be preprocessed by multi-driver source data and then transferred to the trust assessment center in the specified data format. The connection request module, located in the load management terminal, can send connection requests to the master station. The request message includes data from the load management terminal itself. The main station verification module is set in the main station, establishes a connection with the load management terminal, obtains the communication data sent by the load management terminal, and verifies whether the main station retains the context data of the terminal. If it does, the context data is used for authentication; otherwise, the authentication fails. The terminal verification module, located in the load management terminal, can obtain communication data sent by the master station and verify whether the load management terminal retains the context data of the load management terminal. If it does, it will authenticate the context data; otherwise, the authentication will fail. If the authentication verification module confirms that both the load management terminal and the main station are successfully authenticated, then access is granted. The encryption module enables the main station and the load management terminal to hash their respective acquired communication data, generate digital signatures, and timestamp the data after successful access. The encrypted communication data is then sent to the other party. The verification module, load management terminal and main station respectively obtain the communication data and decrypt it, extract the digest of the decrypted original data and compare it, and verify the legality of the timestamp. If both the digest and the timestamp are authenticated, the data is considered safe; otherwise, the communication data is considered to have been tampered with.

6. The system according to claim 5, characterized in that, The step of selecting whether to load the emergency response and event logging program for immune defense based on the test results specifically includes: The equipment safety administrator determines whether the data is abnormal. If so, proceed to the next step; otherwise, it is a false alarm of immune cells, and the immune cell is transferred to the immature immune cell population. Perform security classification on abnormal data, determine whether immediate processing is required based on the security level, and perform disaster recovery backup. If necessary, proceed to the next step; otherwise, log and continue running the program. Determine the type of anomaly that occurred, and check if the data is necessary. If not, discard the data; if so, proceed to the next step. Check whether a memory has been formed from all previously encountered antigens and whether timely countermeasures are taken upon repeated exposure. If so, log the information and continue running; otherwise, proceed to the next step. Perform rapid reconstruction of the system operating environment and restore the previous state; The generated emergency response strategy will be recorded and the results will be fed back.

7. The system according to claim 5, characterized in that, The process of authenticating the context data in the main station verification module and the terminal verification module includes: Import the pre-defined authentication security scoring strategy model standard template library into the main site; The master station sends a data request message through the management terminal. When the master station receives a connection request from the terminal, it will negotiate the access with the terminal. The negotiation will obtain context data, and then the master station will collect the historical data of the previous connections of the site. Adaptive authentication calculates the risk associated with authentication attempts based on factors established during user type and system settings. If the risk is below a preset first security threshold, the authentication attempt is allowed; if the risk is between the first and second security thresholds, the user is required to provide other authentication methods; if the risk is above the second security threshold, the authentication attempt will be rejected, the attacker will be blocked, or the authentication attempt will be redirected to a secure zone.

8. The system according to claim 5, characterized in that, The verification module includes: The encryption element can generate a timestamp for each communication message and generate a digital signature by hashing the data and timestamp. The NTRU encryption system is used to encrypt the communication data in the smart grid. After encryption, the total length is appended to the message header, and then the message data is sent to the receiver. The validity verification element involves the master station receiving a message, obtaining the encrypted communication data, timestamp, and digital signature, decrypting it, and determining the validity of the timestamp. If the timestamp is invalid, the communication data is discarded; if it is valid, the integrity is verified. The integrity verification element is capable of performing integrity verification. It calculates a message digest from the decrypted communication data and timestamp, decrypts the digital signature using the trusted cryptographic module and the peer certificate obtained during the node identity authentication process, and compares it with the calculated message digest. If they are different, the communication data is discarded; if they are the same, the timestamp is removed and plaintext protocol data is obtained.

9. A computer-readable storage medium storing computer-executable instructions for performing the method of any one of claims 1 to 4.

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