Identity authentication system and method for wireless terminal equipment of power distribution network
By using device hardware fingerprint extraction and identity authentication model in the distribution network, using autoencoder and neural network technology to extract device hardware features from CSI and generate hardware fingerprints, the security of the identity authentication system in the existing technology is solved and The problem of insufficient privacy has achieved safe, efficient and stable identity verification of distribution network terminal equipment.
Patent Information
- Application Number
- CN202411493710.2
- Authority / Receiving Office
- CN · China
- Patent Type
- Applications(China)
- Current Assignee / Owner
- Filing Date
- 2024-10-24
- Publication Date
- 2025-02-07
AI Technical Summary
The existing distribution network wireless terminal equipment identity authentication system has shortcomings in terms of security, privacy protection and practical applications, and it is difficult to effectively identify and verify the identity of the equipment, resulting in security risks and unstable operation.
The device hardware fingerprint extraction model and the device identity authentication model are used to extract the device hardware features from the device's channel state information (CSI) through autoencoder and neural network technology, and generate a unique hardware fingerprint, and use the neural network for identity authentication.
It realizes safe, efficient and stable identity verification of distribution network terminal equipment, reduces the risks of node forgery and internal attacks, improves the security and privacy of the system, and reduces operating costs and network burden.
Smart Images
Figure CN119397509A_ABST
Abstract
Description
Technical Field
[0001] The present application relates to the fields of industrial network Internet and mobile communications, and in particular to a system and method for authenticating the identity of wireless terminal equipment in a distribution network. Background Art
[0002] As a complex power system, the distribution network contains a wide variety of terminal devices with different functions. These devices transmit and exchange data through wireless communication technology, forming the "nervous system" of the distribution network. However, in this huge network, how to ensure the authenticity of the identity of each terminal has become a key issue that needs to be solved urgently.
[0003] The identity authentication of terminal devices is not only related to the safe operation of the distribution network, but also an important part of ensuring the stability of power supply. If the identity of the device cannot be effectively identified and verified, it may lead to unauthorized devices accessing the system, causing security risks such as data leakage and malicious control, and thus threatening the normal operation of the entire distribution network. Summary of the invention
[0004] The purpose of the embodiments of the present invention is to provide a distribution network wireless terminal device identity authentication system and method, aiming to solve the shortcomings of the existing distribution network wireless terminal device identity authentication system in terms of security, privacy protection and practical application, and to achieve safe, efficient and stable identity authentication of distribution network terminal devices by utilizing device hardware fingerprints for identity authentication.
[0005] In order to solve the above technical problems, the technical solution adopted by the present invention is:
[0006] The embodiment of the present invention provides a distribution network wireless terminal device identity authentication system, including: a device hardware fingerprint extraction model and a device identity authentication model;
[0007] The device hardware fingerprint extraction model is used to:
[0008] Receive CSI data from two devices as input at the same time: CSI data from a known legitimate device and CSI data from the device to be authenticated;
[0009] The autoencoder is used to encode and compress the input and decode and reconstruct it, and the hardware features of each device are extracted as the unique hardware fingerprint of the device;
[0010] The device authentication model is used to:
[0011] Use neural networks to compare the extracted hardware fingerprints of two devices;
[0012] Based on the comparison results of the neural network, a judgment result is output, indicating whether the device to be authenticated is a legitimate device.
[0013] In some embodiments, the device hardware fingerprint extraction model is further used to:
[0014] The twin network structure is used to process two inputs simultaneously, and the extracted device hardware features are compared using a triplet loss function to calculate the distance metric between the two inputs.
[0015] In some embodiments, in the device authentication model, the neural network utilized includes an encoder and a multi-layer perceptron network of the device hardware fingerprint extraction model.
[0016] Some embodiments of the present invention also provide a method for authenticating the identity of a wireless terminal device in a power distribution network, using the above-mentioned wireless terminal device authentication system for the power distribution network; the method for authenticating the identity of a wireless terminal device in a power distribution network comprises two steps: extracting the hardware fingerprint of the device and authenticating the identity of the device;
[0017] The device hardware fingerprint extraction step includes:
[0018] Receive CSI data from two devices as input at the same time: CSI data from a known legitimate device and CSI data from the device to be authenticated;
[0019] The autoencoder is used to encode and compress the input and decode and reconstruct it, and the hardware features of each device are extracted as the unique hardware fingerprint of the device;
[0020] The device identity authentication step includes:
[0021] Use neural networks to compare the extracted hardware fingerprints of two devices;
[0022] Based on the comparison results of the neural network, a judgment result is output, indicating whether the device to be authenticated is a legitimate device.
[0023] In some embodiments, the device hardware fingerprint extraction step further includes:
[0024] The twin network structure is used to process two inputs simultaneously, and the extracted device hardware features are compared using a triplet loss function to calculate the distance metric between the two inputs.
[0025] In some embodiments, the method for authenticating the identity of a wireless terminal device in a power distribution network further includes:
[0026] If the device to be authenticated is a legitimate device, the system allows it to access the network;
[0027] If the device to be authenticated is an illegal device, the system will refuse to allow it to connect to the network and will promptly respond with an alarm to alert the administrator that an unregistered device is attempting to access the network.
[0028] In some embodiments, the method for authenticating the identity of a wireless terminal device in a power distribution network further includes:
[0029] If the device to be authenticated is a legitimate device, the system updates the legitimate device fingerprint database using the extracted device hardware fingerprint.
[0030] As a complex power system, the distribution network contains a wide variety of terminal devices with different functions. These devices transmit and exchange data through wireless communication technology, forming the "nervous system" of the distribution network. However, in this huge network, how to ensure the authenticity of the identity of each terminal has become a key issue that needs to be solved urgently.
[0031] The identity authentication of terminal devices is not only related to the safe operation of the distribution network, but also an important part of ensuring the stability of power supply. If the identity of the device cannot be effectively identified and verified, it may lead to unauthorized devices accessing the system, causing security risks such as data leakage and malicious control, and thus threatening the normal operation of the entire distribution network.
[0032] At present, the identity authentication of wireless terminal devices in the distribution network mainly adopts the following two schemes:
[0033] Traffic feature-based identity authentication scheme: This scheme extracts device-specific behavioral features, such as communication frequency, duration, and content, by real-time monitoring and analysis of the communication traffic of terminal devices, and uses machine learning or artificial intelligence technology to build a device behavior model to determine the device identity and status. This scheme has the advantages of being non-perceptual and non-invasive, and has strong adaptability. It can be applied to distribution networks of various types and sizes, and can detect abnormal device behavior in real time. However, misjudgments may occur in complex network environments, and continuous learning is required to adapt to changes in device behavior patterns.
[0034] Identity authentication scheme based on encryption mechanism: This scheme uses cryptography technology to encrypt and decrypt the identity information of terminal devices to ensure the security of identity information during transmission. It usually requires the installation of a security chip or module on the terminal device for key generation, storage and calculation. This scheme provides high security, high efficiency and high reliability, and can effectively prevent identity information from being tampered with or forged. It is suitable for large-scale equipment management and distribution networks with high security requirements. However, it also faces challenges such as high hardware requirements, high costs, and the need to regularly update keys and security policies.
[0035] Although the authentication scheme based on traffic characteristics and encryption mechanism can realize device authentication to a certain extent, it still has some inherent defects and limitations:
[0036] Traffic feature-based authentication schemes are highly dependent on the communication behavior of terminal devices. However, these behaviors may be affected by a variety of factors such as network environment, device status, and user operations, resulting in unstable, inaccurate, or non-unique traffic features. This uncertainty may significantly reduce the accuracy and reliability of authentication. More seriously, the scheme is vulnerable to attacks such as traffic analysis, traffic forgery, and traffic replay. These potential security risks pose a severe challenge to the security and privacy of authentication.
[0037] The authentication scheme based on encryption mechanism relies heavily on the key generation, storage and management process, which may have potential vulnerabilities and risks. For example, if the key generation algorithm has weaknesses, defects or lacks sufficient randomness, the generated key may be easily cracked, predicted or even reused. In addition, in order to reduce the risk of key leakage during storage and management, the scheme usually requires the installation of additional hardware security modules on the terminal equipment, which will undoubtedly increase the operating cost of the distribution network, thus hindering the actual application and promotion of the scheme.
[0038] In order to solve the above problems, the present invention proposes a distribution network wireless terminal device identity authentication system and method. The present invention generates a specific device hardware fingerprint by extracting the inherent and unforgeable physical characteristics of the device hardware itself to identify the device individual, thereby effectively reducing the vulnerability of the distribution network to node forgery and internal attacks. Compared with the solution based on traffic characteristics and encryption mechanism, using device hardware fingerprint for device identity authentication has the following three advantages:
[0039] High security: the hardware fingerprint of the device is determined by the physical properties and production process of the device, is not affected by the software or network environment, and is difficult to tamper with or forge;
[0040] Good stability. The hardware fingerprint of the device does not change significantly with the device usage time, status or environment changes, maintaining the consistency of the device identity.
[0041] High privacy: the collection and extraction of device hardware fingerprints does not involve user personal information or sensitive data, avoiding privacy leaks and compliance risks.
[0042] The present invention provides a distribution network wireless terminal device identity authentication system and method, and proposes a device hardware fingerprint extraction model. The model can extract a low-dimensional feature representation reflecting the device hardware characteristics from the device's channel state information (CSI) by reconstructing the input and calculating the distance metric between the two inputs in the feature space, and generate a fingerprint identifier that can uniquely identify the device. The model can extract inherent and unforgeable physical features from the distribution network terminal device hardware, and generate a specific device fingerprint with device specificity, time stability and environmental stability.
[0043] The present invention provides a distribution network wireless terminal device identity authentication system and method, and proposes a device identity authentication model, which checks the legitimacy of the terminal device by comparing the similarity of the device hardware fingerprint, thereby realizing instant confirmation of the device identity. The model can effectively measure the matching degree between the hardware fingerprint of the device to be checked and the fingerprint of the legitimate device, and ensure the accuracy of the authentication.
[0044] The present invention provides a distribution network wireless terminal device identity authentication system and method. The system performs safe, efficient and stable identity authentication on distribution network terminal devices based on the device hardware fingerprint extraction model and device identity authentication model proposed by the present invention. The system can realize rapid authentication of multiple devices, while ensuring high security and high privacy, and reducing the communication burden of the distribution network system.
[0045] The present invention provides a distribution network wireless terminal device identity authentication system and method, which does not require the installation of additional hardware modules or software upgrades on the terminal device, effectively reducing the production cost and operating load of the device. At the same time, the present invention can authenticate multiple devices at the same time without complex communications, reducing the network burden of identity authentication. This feature has important practical application value and necessity for large-scale, dynamic, and distributed terminal devices in the distribution network. BRIEF DESCRIPTION OF THE DRAWINGS
[0046] In order to more clearly illustrate the technical solutions in the present disclosure, the following briefly introduces the drawings required for use in some embodiments of the present disclosure. Obviously, the drawings described below are only drawings of some embodiments of the present disclosure. For ordinary technicians in this field, other drawings can also be obtained based on these drawings. In addition, the drawings described below can be regarded as schematic diagrams, and are not limitations on the actual size of the products involved in the embodiments of the present disclosure, the actual process of the method, etc.
[0047] Figure 1 A schematic diagram of a device hardware fingerprint extraction model architecture according to some embodiments of the present disclosure;
[0048] Figure 2A schematic diagram of a device identity authentication model architecture according to some embodiments of the present disclosure;
[0049] Figure 3 The present invention is a schematic diagram of the architecture of a wireless terminal device identity authentication system for a power distribution network according to some embodiments of the present disclosure. DETAILED DESCRIPTION
[0050] The following will be combined with the accompanying drawings to clearly and completely describe the technical solutions in some embodiments of the present disclosure. Obviously, the described embodiments are only part of the embodiments of the present disclosure, rather than all the embodiments. Based on the embodiments provided by the present disclosure, all other embodiments obtained by ordinary technicians in this field belong to the scope of protection of the present disclosure.
[0051] Unless the context requires otherwise, throughout the specification and claims, the term "including" is to be interpreted as an open, inclusive meaning, that is, "including, but not limited to". In the description of the specification, the terms "one embodiment", "some embodiments", "exemplary embodiments", "examples" or "some examples" and the like are intended to indicate that specific features, structures, materials or characteristics associated with the embodiment or example are included in at least one embodiment or example of the present disclosure. The schematic representations of the above terms do not necessarily refer to the same embodiment or example. In addition, the specific features, structures, materials or characteristics described may be included in any one or more embodiments or examples in any appropriate manner.
[0052] The embodiment of the present invention provides a distribution network wireless terminal device identity authentication system, such as Figure 3 As shown, it includes: device hardware fingerprint extraction model and device identity authentication model.
[0053] In some examples, such as Figure 1 As shown, the device hardware fingerprint extraction model is used to implement steps S100 to S200.
[0054] S100, simultaneously receiving CSI data of two devices as input: CSI data of a known legitimate device and CSI data of a device to be authenticated.
[0055] S200 uses an autoencoder to encode and compress the input and decode and reconstruct it, and extracts the hardware features of each device as the unique hardware fingerprint of the device.
[0056] In step S200, the device hardware fingerprint extraction model passes two inputs to encoders with the same weights respectively, and then performs encoding compression and decoding reconstruction on the two inputs.
[0057] In step S200 , the autoencoder used is a previously trained autoencoder.
[0058] During steps S100 to S200, the device hardware fingerprint extraction model discards less important information and effectively extracts the device hardware characteristics contained in the CSI, thereby ensuring that the authentication system uses the most representative and distinguishing features of the device during the authentication process.
[0059] In some examples, such as Figure 2 As shown, the device identity authentication model is used to implement steps S300 to S400.
[0060] S300,utilizes neural network to compare the extracted hardware fingerprints of two,devices.
[0061] Exemplarily, in step S300, the neural network used includes an encoder and a multi-layer perceptron network of the device hardware fingerprint extraction model, and the multi-layer perceptron network is a supervised trained multi-layer perceptron network. The neural network is optimized to accurately evaluate the similarity between two device hardware fingerprints, so as to determine whether they are from the same device. This comparison method can not only capture subtle differences, but also adapt to slight changes that may occur in different operating environments.
[0062] S400, based on the comparison result of the neural network, output a determination result, indicating whether the device to be authenticated is a legitimate device.
[0063] During steps S300 to S400 , the device identity authentication model allows the system to quickly and accurately verify the device identity without complex manual intervention or traditional key management.
[0064] The invention provides a distribution network wireless terminal device identity authentication system, and proposes a device hardware fingerprint extraction model. The model can extract a low-dimensional feature representation reflecting the device hardware characteristics from the device's channel state information (CSI) by reconstructing the input and calculating the distance metric between the two inputs in the feature space, and generate a fingerprint identifier that can uniquely identify the device. The model can extract inherent and unforgeable physical features from the distribution network terminal device hardware, and generate a specific device fingerprint with device specificity, time stability and environmental stability.
[0065] The invention provides a distribution network wireless terminal device identity authentication system, and proposes a device identity authentication model, which checks the legitimacy of the terminal device by comparing the similarity of the device hardware fingerprint, thereby realizing instant confirmation of the device identity. The model can effectively measure the matching degree between the hardware fingerprint of the device to be checked and the fingerprint of the legitimate device, and ensure the accuracy of the authentication.
[0066] The present invention provides a distribution network wireless terminal device identity authentication system, which performs safe, efficient and stable identity authentication on distribution network terminal devices based on the device hardware fingerprint extraction model and device identity authentication model proposed by the present invention. The system can realize rapid authentication of multiple devices, while ensuring high security and high privacy, and reducing the communication burden of the distribution network system.
[0067] In some examples, the device hardware fingerprint extraction model is also used to implement step S210.
[0068] S210, utilizes the twin network structure to process two inputs simultaneously, uses the triplet loss function to compare the extracted device hardware features, and then calculates the distance metric between the two inputs.
[0069] In step S210, the model is trained using a triplet loss function, which is capable of calculating a distance metric between two inputs, so that the model can generate device hardware features that are close to each other for CSI from the same device, and generate significantly different device hardware features for CSI from different devices.
[0070] like Figure 1 As shown in the figure, the device hardware fingerprint extraction model proposed in the present invention adopts an innovative architecture combining an autoencoder and a twin network. The model can effectively compare the features of the channel state information (CSI) input of two devices and generate a distinguishing device hardware fingerprint.
[0071] The device hardware fingerprint extraction model proposed in the present invention can not only effectively capture the unique hardware characteristics of the device, but also establish a clear distinction between different devices. It provides an efficient and reliable hardware fingerprint extraction method for distribution network wireless terminal devices, laying a solid foundation for subsequent identity authentication.
[0072] An embodiment of the present invention further provides a method for authenticating a wireless terminal device in a power distribution network, which uses the above-mentioned wireless terminal device authentication system; the method for authenticating a wireless terminal device in a power distribution network includes two steps: device hardware fingerprint extraction and device identity authentication.
[0073] In some examples, the device hardware fingerprint extraction step includes: S100-S200.
[0074] S100, simultaneously receiving CSI data of two devices as input: CSI data of a known legitimate device and CSI data of a device to be authenticated.
[0075] S200 uses an autoencoder to encode and compress the input and decode and reconstruct it, and extracts the hardware features of each device as the unique hardware fingerprint of the device.
[0076] In some examples, the device identity authentication step includes: S300~S400.
[0077] S300,utilizes neural network to compare the extracted hardware fingerprints of two,devices.
[0078] S400, based on the comparison result of the neural network, output a determination result, indicating whether the device to be authenticated is a legitimate device.
[0079] The beneficial effects that can be achieved by the distribution network wireless terminal device identity authentication method provided in some embodiments of the present invention are the same as the beneficial effects that can be achieved by the distribution network wireless terminal device identity authentication system provided in some of the above embodiments, and will not be repeated here.
[0080] In some examples, the device hardware fingerprint extraction step also includes: S210.
[0081] S210, utilizes the twin network structure to process two inputs simultaneously, uses the triplet loss function to compare the extracted device hardware features, and then calculates the distance metric between the two inputs.
[0082] The beneficial effects that can be achieved by the distribution network wireless terminal device identity authentication method provided in some embodiments of the present invention are the same as the beneficial effects that can be achieved by the distribution network wireless terminal device identity authentication system provided in some of the above embodiments, and will not be repeated here.
[0083] In some examples, the distribution network wireless terminal device identity authentication method also includes: S410~S420.
[0084] S410: If the device to be authenticated is a legitimate device, the system allows it to access the network.
[0085] S420, if the device to be authenticated is an illegal device, that is, an unknown device, the system will refuse to allow it to connect to the network, and respond with an alarm in a timely manner to remind the administrator that an unregistered device is trying to access the network.
[0086] A method for authenticating a wireless terminal device in a distribution network provided by the present invention provides a highly secure and highly private identity authentication service for the distribution network system. When a malicious terminal device attempts to connect to the distribution network system, the present invention can quickly and accurately respond to alarms, promptly cut off malicious connections, and effectively prevent potential security threats. The present invention enables the distribution network system to support secure information exchange between communication entities and ensure the remote communication security of each communication party. This not only improves the security and reliability of the entire distribution network, but also provides users with more reliable power services. The application of the present invention helps to build a safer and more stable smart grid system, and provides important technical support for the digital transformation and intelligent development of the power industry.
[0087] In some examples, the distribution network wireless terminal device identity authentication method also includes: S411.
[0088] S411, if the device to be authenticated is a legitimate device, the system updates the legitimate device fingerprint library by using the extracted device hardware fingerprint. By continuously updating the legitimate device fingerprint library, the validity of the legitimate device fingerprint library can be maintained.
[0089] After establishing a legal device fingerprint library, in step S300, the established known legal device fingerprint library can be used to check the legitimacy of the device using the device identity authentication model. The method provided by the present invention not only improves the security and reliability of authentication, but also realizes dynamic update and real-time monitoring, providing an efficient and secure identity authentication solution for wireless terminal devices in the distribution network.
[0090] Finally, it should be noted that the above embodiments are only used to illustrate the technical solution of the present invention rather than to limit it. Other modifications or equivalent substitutions made to the technical solution of the present invention by ordinary technicians in the field should be included in the scope of the claims of the present invention as long as they do not depart from the spirit and scope of the technical solution of the present invention.
Claims
1. A distribution network wireless terminal device identity authentication system, characterized in that: include: Device hardware fingerprint extraction model and device identity authentication model; The device hardware fingerprint extraction model is used to: Receive CSI data from two devices as input at the same time: CSI data from a known legitimate device and CSI data from the device to be authenticated; The autoencoder is used to encode and compress the input and decode and reconstruct it, and the hardware features of each device are extracted as the unique hardware fingerprint of the device; The device authentication model is used to: Use neural networks to compare the extracted hardware fingerprints of two devices; Based on the comparison results of the neural network, a judgment result is output, indicating whether the device to be authenticated is a legitimate device.
2. A distribution network wireless terminal device identity authentication system as claimed in claim 1, characterized in that: The device hardware fingerprint extraction model is also used to: The twin network structure is used to process two inputs simultaneously, and the extracted device hardware features are compared using a triplet loss function to calculate the distance metric between the two inputs.
3. A distribution network wireless terminal device identity authentication system as claimed in claim 1, characterized in that: In the device identity authentication model, the neural network utilized includes an encoder and a multi-layer perceptron network of the device hardware fingerprint extraction model.
4. A method for authenticating the identity of a wireless terminal device in a distribution network, characterized in that: Using the distribution network wireless terminal device identity authentication system as described in any one of claims 1 to 3; The method for authenticating the identity of a wireless terminal device in a power distribution network comprises: There are two steps: device hardware fingerprint extraction and device identity authentication; The device hardware fingerprint extraction step includes: Receive CSI data from two devices as input at the same time: CSI data from a known legitimate device and CSI data from the device to be authenticated; The autoencoder is used to encode and compress the input and decode and reconstruct it, and the hardware features of each device are extracted as the unique hardware fingerprint of the device; The device identity authentication step includes: Use neural networks to compare the extracted hardware fingerprints of two devices; Based on the comparison results of the neural network, a judgment result is output, indicating whether the device to be authenticated is a legitimate device.
5. A method for authenticating the identity of a wireless terminal device in a power distribution network as claimed in claim 4, characterized in that: The device hardware fingerprint extraction step further includes: The twin network structure is used to process two inputs simultaneously, and the extracted device hardware features are compared using a triplet loss function to calculate the distance metric between the two inputs.
6. A method for authenticating the identity of a wireless terminal device in a power distribution network as claimed in claim 4, characterized in that: The method for authenticating the identity of a wireless terminal device in a power distribution network further includes: If the device to be authenticated is a legitimate device, the system allows it to access the network; If the device to be authenticated is an illegal device, the system will refuse to allow it to connect to the network and will promptly respond with an alarm to alert the administrator that an unregistered device is attempting to access the network.
7. A method for authenticating the identity of a wireless terminal device in a power distribution network as claimed in claim 4, characterized in that: The method for authenticating the identity of a wireless terminal device in a power distribution network further includes: If the device to be authenticated is a legitimate device, the system updates the legitimate device fingerprint database using the extracted device hardware fingerprint.