An AMI information security transmission method for power system based on improved endogenous security

Abstract

The application discloses an AMI information security transmission method for power system based on improved endogenous security, and the method is as follows: a message segmentation algorithm is used to randomly divide a message into three sub-messages with different lengths; a heterogeneous redundant encryption executor is used to process the three sub-messages, three sub-ciphertexts and a message authentication code are obtained, and are combined into AEP and sent to a data concentrator; the data concentrator decomposes the AEP to obtain the three sub-ciphertexts and the message authentication code, processes the three sub-ciphertexts by using a heterogeneous redundant decryption executor, and obtains three sub-messages; the data concentrator combines the sub-messages into an unauthenticated message, a message authentication function processes the unauthenticated message to obtain MAC1, the MAC is compared with the MAC1, if the same, the message is output, and if different, the information has been tampered with and the information is re-sent. The method can realize efficient and stable AMI information security transmission, and effectively guarantee the overall security of the system.

Description

Technical Field

[0001] This invention belongs to the field of power system information security, and relates to a method for secure transmission of information in an advanced measurement system (AMI) of a power system, specifically a method for secure transmission of AMI information in a power system based on improved intrinsic security. Background Technology

[0002] Against the backdrop of global energy transition and smart grid construction, AMI (Automatic Management System) has become an important component of the new power system. Through smart meters, communication networks, and data management platforms, AMI helps achieve intelligent matching between user electricity demand and grid supply capacity, supporting real-time data collection, remote control, and two-way information exchange. This not only improves grid operating efficiency but also provides support in peak load management, power outage management, and energy use optimization. Furthermore, AMI promotes the application of distributed energy resources and microgrids, making the integration and utilization of renewable energy more flexible and intelligent. Therefore, AMI plays an irreplaceable role in the operation and maintenance of power systems and is a key link in realizing smart energy management.

[0003] With the widespread application of Access Control Machines (AMIs) in power systems, the importance of secure information transmission has become increasingly prominent. AMI systems frequently transmit large amounts of user electricity consumption data, including sensitive information such as electricity usage habits and electricity consumption. If this data is tampered with or leaked, it not only affects user privacy but may also jeopardize the operational stability of the power system. More seriously, AMIs connect a vast array of power equipment and user terminals, becoming potential entry points for cyberattacks and thus facing multiple threats, including data tampering and malicious attacks. Effective secure information transmission methods can guarantee the integrity, confidentiality, and availability of information, ensure the authenticity and real-time nature of information transmission, and prevent cyberattacks from damaging the power grid. These are crucial safeguards for the stable and safe operation of the power system.

[0004] Traditional AMI (Automatic Management Interface) information security transmission methods have significant limitations in the face of complex network attacks and ever-changing security threats, struggling to effectively defend against zero-day attacks and consuming high resources. Although intrinsic security has advantages such as autonomous defense and strong adaptability, its direct application in power systems faces problems such as high computational overhead and poor hardware compatibility. Summary of the Invention

[0005] This invention addresses security issues such as data leakage, malicious attacks, and tampering encountered during AMI information transmission in power systems. It provides a method for secure AMI information transmission in power systems based on improved intrinsic security. This method meets the high real-time and low-power consumption requirements of power systems for information transmission, achieving efficient and stable secure AMI information transmission and effectively ensuring the overall security of the system.

[0006] The objective of this invention is achieved through the following technical solution:

[0007] A method for secure transmission of AMI information in a power system based on improved intrinsic security includes the following steps:

[0008] Step S1: The smart meter collects data, designs a message segmentation algorithm based on chaotic mapping, and uses this algorithm to segment message M. S The message is randomly divided into three sub-messages of different lengths: M1, M2, and M3. The specific steps are as follows:

[0009] Step S11: The smart meter collects data and sends message M. S The message is sent to the message segmentation program and enters the random message segmentation stage.

[0010] Step S12: Determine the system parameters of the chaotic map: Set the initial value (x,y,z) of the Lorenz chaotic map with parameter transformation to (x0,y0,z0), and set the parameters σ, ρ, and β to σ = a·σ′ + k σ ·Dσ、ρ=b·ρ′+k ρ ·Dρ、β=c·β′+k β ·Dβ, where (a,b,c)=(0,1,1), k σ =1,2,…,400、k ρ =0, k ρ =0;

[0011] Step S13: Establish an unbounded Markov random field for the message: Message M S Converted to the corresponding hexadecimal ASCII code, each message byte is used as a node in the Markov random field. To ensure that the node distribution is random and unpredictable, the three-dimensional coordinates of the node are obtained based on the Lorenz chaotic mapping of the parameter transformation, and then the boundless Markov random field of the message is established.

[0012] Step S14: Calculate the potential function φ(i) = -log(P(x) for each node in the Markov random field. i ), where P(x i ) is the character x i The frequency of occurrence;

[0013] Step S15: Calculate the boundary potential function ψ(i,j) = exp(-d(x) between nodes in the Markov random field. i ,x j ), where d(x) i ,x j Node x i and node x j The distance between them;

[0014] Step S16: Randomly group the nodes in the Markov random field: Randomly assign an initial group to each node, set the total number of groups num_groups = m, and the number of nodes in each group group_size = n;

[0015] Step S17: Update Group State: For node i, calculate the sum of its potential function value and edge potential function value in the current group to obtain the current energy current_energy; traverse all candidate groups g, calculate the energy difference energy_diff after node i moves to group g, which is the difference between node i's energy in group g and its current energy; calculate the transition probability transition_prob based on the energy difference and perform normalization processing; sample and update groups, sample from candidate groups according to the transition probability, and update the group state of node i;

[0016] Step S18: Repeat step S17 several times until the system reaches a stable distribution, resulting in three sub-messages M1, M2 and M3;

[0017] Step S2: The smart meter uses a heterogeneous redundant encryption execution entity to process the three sub-messages and message M. S The process yields three sub-ciphertexts, SE1, SE2, and SE3, along with the Message Authentication Code (MAC). These sub-ciphertexts and the MAC are then combined to form an Authentication Encryption Packet (AEP) and sent to the data concentrator. The specific steps are as follows:

[0018] Step S21: Message encryption operation: The smart meter sends the sub-messages M1, M2 and M3 into the encryption execution body, and performs encryption operations SE1=Symmetric_encrypt1(M1), SE2=Symmetric_encrypt2(M2) and SE3=Symmetric_encrypt3(M3) to obtain three sub-ciphertexts SE1, SE2 and SE3;

[0019] Step S22: Message authentication operation: The smart meter will send message M S The message authentication execution body is sent to perform the message authentication operation MAC = MAC(M). S ), obtain the message authentication code (MAC);

[0020] Step S23: The smart meter combines the three sub-ciphertexts SE1, SE2, and SE3 with the message authentication code MAC into an authentication encryption packet AEP and sends the AEP to the data concentrator;

[0021] Step S3: The data concentrator decomposes the AEP to obtain three sub-ciphertexts SE1, SE2, and SE3, along with the message authentication code MAC. A heterogeneous redundant decryption execution unit then processes these three sub-ciphertexts to obtain three sub-messages M1, M2, and M3. The specific steps are as follows:

[0022] Step S31: The data concentrator performs a segmentation operation on the received AEP to obtain three sub-ciphertexts SE1, SE2, SE3 and the message authentication code MAC;

[0023] Step S32: Decryption operation: The data concentrator sends the sub-ciphertexts SE1, SE2 and SE3 into the decryption execution body, performs decryption operations M1=Symmetric_decrypt1(SE1), M2=Symmetric_decrypt2(SE2) and M3=Symmetric_decrypt3(SE3), and obtains three sub-messages M1, M2 and M3;

[0024] Step S4: The data consolidator combines sub-messages M1, M2, and M3 into an unauthenticated message M. R_unauthenticated The message authentication function handles unauthenticated messages M. R_unauthenticated The process involves processing to obtain MAC1. MAC1 is then compared with MAC2. If they match, the message is output; otherwise, it indicates the information has been tampered with and is retransmitted. The specific steps are as follows:

[0025] Step S41: The data consolidator combines sub-messages M1, M2, and M3 into an unauthenticated message M. R_unauthenticated ;

[0026] Step S42: Unauthenticated message authentication operation: The data concentrator will authenticate the unauthenticated message M. R_unauthenticated The message authentication execution body is sent to perform the message authentication operation MAC = MAC(M). R_unauthenticated ), and obtain the message authentication code MAC1 of the unauthenticated message;

[0027] Step S43: The data concentrator compares the message authentication code (MAC) with the message authentication code (MAC1) of the unauthenticated message. If they are the same, it outputs message M. R =M R_unauthenticated If they are different, it means the information has been tampered with and should be resent.

[0028] Compared with the prior art, the present invention has the following advantages:

[0029] 1. This invention optimizes the intrinsic security mechanism, enabling it to have stronger autonomous defense capabilities and resource efficiency, thereby better adapting to the high real-time and low power consumption requirements of power systems for information transmission.

[0030] 2. Through the method of the present invention, the integrity, confidentiality and system stability of AMI data during transmission are effectively guaranteed, and the information security level of the power system is significantly improved.

[0031] 3. Compared with the high resource consumption of traditional intrinsic security protection measures, the method proposed in this invention reduces the resource consumption of protection measures by introducing a message segmentation algorithm, meets the requirements of power system for real-time performance and low power consumption, and effectively ensures the security of AMI information transmission. Attached Figure Description

[0032] Figure 1 Here is an overall flowchart of a power system AMI information security transmission method based on improved intrinsic security;

[0033] Figure 2 This is a flowchart illustrating the specific process for secure transmission of AMI information in power systems based on improved intrinsic security. Detailed Implementation

[0034] The technical solution of the present invention will be further described below with reference to the accompanying drawings, but it is not limited thereto. Any modifications or equivalent substitutions to the technical solution of the present invention that do not depart from the spirit and scope of the technical solution of the present invention should be covered within the protection scope of the present invention.

[0035] This invention provides a method for secure transmission of AMI information in a power system based on improved intrinsic security, such as... Figure 1 As shown, the method includes the following steps:

[0036] Step S1: The smart meter collects data, designs a message segmentation algorithm based on chaotic mapping, and uses this algorithm to segment message M. S The message is randomly divided into three sub-messages of different lengths: M1, M2, and M3.

[0037] Step S2: The smart meter uses a heterogeneous redundant encryption execution entity to process the three sub-messages and message M. S The process yields three sub-ciphertexts, SE1, SE2, and SE3, along with the message authentication code (MAC). These sub-ciphertexts and the MAC are then combined into an authentication encryption packet (AEP) and sent to the data concentrator.

[0038] Step S3: The data concentrator decomposes the AEP to obtain three sub-ciphertexts SE1, SE2, and SE3 and the message authentication code MAC. The heterogeneous redundant decryption execution unit processes the three sub-ciphertexts to obtain three sub-messages M1, M2, and M3.

[0039] Step S4: The data consolidator combines sub-messages M1, M2, and M3 into an unauthenticated message M. R_unauthenticated The message authentication function handles unauthenticated messages M. R_unauthenticatedThe process is performed to obtain MAC1. The MAC is compared with MAC1. If they are the same, the message is output. If they are different, it means that the information has been tampered with and the information is resent.

[0040] like Figure 2 As shown, the specific implementation steps are as follows:

[0041] Step S1: The smart meter collects data and sends message M. S The message is sent to the message segmentation program and enters the random message segmentation stage.

[0042] Step S2: Determine the system parameters of the chaotic map. Set the initial values ​​(x,y,z) of the Lorenz chaotic map with parameter transformation to (x0,y0,z0), and set the parameters σ, ρ, and β to σ = a·σ′ + k. σ ·Dσ、ρ=b·ρ′+k ρ ·Dρ、β=c·β′+k β ·Dβ, where (a,b,c)=(0,1,1), k σ =1,2,…,400、k ρ =0, k ρ =0.

[0043] Step S3: Establish an unbounded Markov random field for the message. Send message M... S The data is converted to the corresponding hexadecimal ASCII code, with each message byte serving as a node in the Markov random field. To ensure the randomness and unpredictability of the node distribution, the three-dimensional coordinates of the nodes are obtained based on the Lorenz chaotic mapping with parameter transformation, thereby establishing an unbounded Markov random field for the message.

[0044] Step S4: Calculate the potential function of each node in the Markov random field. The frequency-based potential function ensures that high-frequency characters have lower potential function values, making these characters more likely to maintain their positions during segmentation. This reduces the frequent segmentation of high-frequency characters, preserving the semantic structure and readability of the message. Therefore, the potential function of each node is φ(i) = -log(P(x...). i ), where P(x i ) is the character x i Frequency of occurrence.

[0045] Step S5: Calculate the boundary potential function between nodes in the Markov random field. The distance-based boundary potential function quantifies the spatial distance between nodes, ensuring that characters that are closer together are more likely to be assigned to the same group. This method utilizes the spatial correlation between characters, increasing the rationality of segmentation and ensuring the spatial consistency of message segmentation results. Therefore, the boundary potential function between nodes is ψ(i,j)=exp(-d(x i ,x j), where d(x) i ,x j Node x i and node x j The distance between them.

[0046] Step S6: Randomly group the nodes in the Markov random field. Randomly assign an initial group to each node, setting the total number of groups num_groups = m, and the number of nodes in each group group_size = n.

[0047] Step S7: Update the group state. For node i, calculate the sum of its potential function value and edge potential function value in the current group to obtain the current energy `current_energy`. Traverse all candidate groups `g` and calculate the energy difference `energy_diff` after node i moves to group `g`. This energy difference is the difference between node i's energy in group `g` and its current energy. Calculate the transition probability `transition_prob` based on the energy difference. The transition probability is proportional to the negative exponent of the energy difference and is normalized. Sample and update the group: Based on the transition probability, sample from the candidate groups and update the group state of node i.

[0048] Step S8: Repeat step S7 several times until the system reaches a stable distribution, resulting in three sub-messages M1, M2 and M3.

[0049] Step S9: Message Encryption Operation. The smart meter sends sub-messages M1, M2, and M3 into the encryption execution body, performs encryption operations SE1 = Symmetric_encrypt1(M1), SE2 = Symmetric_encrypt2(M2), and SE3 = Symmetric_encrypt3(M3), and obtains three sub-ciphertexts SE1, SE2, and SE3.

[0050] Step S10: Message authentication calculation. The smart meter will process message M. S The message authentication execution body is sent to perform the message authentication operation MAC = MAC(M). S ), and obtain the message authentication code (MAC).

[0051] Step S11: The smart meter combines the three sub-ciphertexts SE1, SE2, and SE3 with the message authentication code MAC into an authentication encryption packet AEP and sends the AEP to the data concentrator.

[0052] Step S12: The data concentrator performs a segmentation operation on the received AEP to obtain three sub-ciphertexts SE1, SE2, SE3 and the message authentication code MAC.

[0053] Step S13: Decryption operation. The data concentrator sends the sub-ciphertexts SE1, SE2 and SE3 into the decryption execution body, performs decryption operations M1=Symmetric_decrypt1(SE1), M2=Symmetric_decrypt2(SE2) and M3=Symmetric_decrypt3(SE3), and obtains three sub-messages M1, M2 and M3.

[0054] Step S14: The data consolidator combines sub-messages M1, M2, and M3 into an unauthenticated message M. R_unauthenticated .

[0055] Step S15: Authentication operation for unauthenticated message. The data concentrator will process the unauthenticated message M. R_unauthenticated The message authentication execution body is sent to perform the message authentication operation MAC = MAC(M). R_unauthenticated ) Received the message authentication code MAC1 for the unauthenticated message.

[0056] Step S16: The data concentrator compares the message authentication code (MAC) with the message authentication code (MAC1) of the unauthenticated message. If they are the same, it outputs message M. R =M R_unauthenticated If the values ​​are different, it means the information has been tampered with and needs to be resent.

Claims

1. A method for secure transmission of AMI information in a power system based on improved intrinsic security, characterized in that... The method includes the following steps: Step S1: The smart meter collects data, designs a message segmentation algorithm based on chaotic mapping, and uses this algorithm to segment the messages. Randomly divide into three sub-messages of different lengths. Sub-message and sub-messages The specific steps are as follows: Step S11: The smart meter collects data and sends a message. The message is sent to the message segmentation program and enters the random message segmentation stage. Step S12: Determine the system parameters of the chaotic map: Initialize the Lorenz chaotic map with transformed parameters. Set as Parameters σ, ρ, and β are set to , , ,in , , , ; Step S13: Establish an unbounded Markov random field for the message: send the message Converted to the corresponding hexadecimal ASCII code, each message byte is used as a node in the Markov random field. To ensure that the node distribution is random and unpredictable, the three-dimensional coordinates of the node are obtained based on the Lorenz chaotic mapping of the parameter transformation, and then the boundless Markov random field of the message is established. Step S14: Calculate the potential function of each node in the Markov random field. ,in, It is a character The frequency of occurrence; Step S15: Calculate the boundary potential function between nodes in the Markov random field. ,in, node and nodes The distance between them; Step S16: Randomly group the nodes in the Markov random field: Randomly assign an initial group to each node, and set the total number of groups. The number of nodes in each group ; Step S17: Update group status: for node Calculate the sum of its potential function value and edge potential function value under the current group to obtain the current energy. ; Traverse all candidate groups compute nodes Move to group Energy difference after This energy difference is the node In groups The difference between the current energy and the energy below; calculate the transition probability based on the energy difference. The data is then normalized; sampling and updating of the groups are performed, and nodes are updated by sampling from the candidate groups based on the transition probability. Grouping status; Step S18: Repeat step S17 several times until the system reaches a stable distribution, resulting in three sub-messages. , and ; Step S2: The smart meter uses a heterogeneous redundant encryption executor to process the three sub-messages and the message. After processing, three ciphertexts were obtained. , , With message authentication code The ciphertext is then combined with the message authentication code to form an authentication encryption packet. Send to the data concentrator; Step S3: The data concentrator will Decomposition yields three ciphertexts. , , With message authentication code The three sub-ciphertexts are processed using a heterogeneous redundant decryption execution unit to obtain three sub-messages. , and ; Step S4: The data concentrator will divide the sub-messages , and Combined into an unauthenticated message The message authentication function handles unauthenticated messages. Processing is performed to obtain ,Will and The comparison is performed. If they are the same, the message is output; if they are different, it means that the information has been tampered with and the information is resent.

2. The method for secure transmission of AMI information in a power system based on improved intrinsic security according to claim 1, characterized in that... The specific steps of step S2 are as follows: Step S21: Message Encryption Operation: The smart meter will encrypt the sub-message. , and Send it to the encryption execution unit to perform encryption operations. , and Three ciphertexts were obtained. , and ; Step S22: Message authentication operation: The smart meter will send message M S The message is sent to the message authentication execution body to perform the message authentication operation. Receive message verification code ; Step S23: The smart meter transmits three encrypted packets. , and and message verification code Combined into an authentication encryption package And Send to the data concentrator.

3. The method for secure transmission of AMI information in a power system based on improved intrinsic security according to claim 1, characterized in that... The specific steps of step S3 are as follows: Step S31: The data concentrator performs a segmentation operation on the received AEP to obtain three sub-ciphertexts. , , and message verification code ; Step S32: Decryption operation: The data concentrator decrypts the sub-ciphertext. , and Send it to the decryption execution unit to perform decryption operations. , and Three messages were received. , and .

4. The method for secure transmission of AMI information in a power system based on improved intrinsic security according to claim 1, characterized in that... The specific steps of step S4 are as follows: Step S41: The data concentrator will send sub-messages , and Combined into an unauthenticated message ; Step S42: Unauthenticated message authentication operation: The data concentrator will authenticate unauthenticated messages. The message is sent to the message authentication execution body to perform the message authentication operation. Message authentication code for receiving unauthenticated messages ; Step S43: The data concentrator will send the message authentication code. Message authentication code for unauthenticated messages Compare the results; if they match, output a message. If they are different, it means the information has been tampered with and should be resent.

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