Power internet of things device identity authentication method and system based on quantum cloud code

Abstract

The application relates to the technical field of electric power data transmission, and discloses a power internet of things device identity authentication method and system based on quantum cloud codes. The method comprises the following steps: collecting quantum state information via a quantum random number generator, generating an electric power authentication seed and converting the electric power authentication seed into a quantum cloud code initial seed; collecting electric power device identification and characteristic parameters to generate a characteristic vector; expanding the quantum cloud code initial seed into a sub-key sequence, generating an authentication quantum cloud code through quantum entanglement coding and error correction; executing quantum evolution within an authentication time window to generate a dynamic authentication code; performing quantum measurement after receiving a challenge sequence to construct authentication response data; and finally determining an authentication state through a blockchain storage and an intelligent contract. The application combines quantum cryptography and blockchain technology, and realizes a high-security, low-cost and expandable device identity authentication mechanism.

Description

Technical Field

[0001] The present application relates to the field of power data transmission, and in particular to a method and system for authenticating the identity of power Internet of Things devices based on quantum cloud code. Background Art

[0002] With the rapid development of the power Internet of Things (IoT), the number of connected devices is growing exponentially, posing significant challenges to traditional authentication mechanisms. Currently, widely adopted authentication technologies include cryptographic-based certificate authentication, hardware-based device authentication, and biometric-based identity authentication. These authentication technologies are widely used in power systems, ensuring the authenticity of device identities and the security of communications through digital certificates, key management, and encrypted communications. Furthermore, the introduction of blockchain technology provides a decentralized trust foundation for device authentication, and the development of quantum cryptography offers new technical avenues for enhancing authentication security.

[0003] However, related authentication technologies have some shortcomings: first, traditional key management systems are unable to cope with the authentication needs of large-scale devices, and the generation, distribution and update of keys bring huge management overhead; second, authentication schemes based on hardware identification are vulnerable to attacks such as hardware cloning and identification forgery; third, IoT devices have limited computing resources and cannot support complex cryptographic operations; finally, the development of quantum computing poses a potential threat to traditional cryptography, and existing quantum security authentication schemes have not yet been effectively integrated with emerging technologies such as blockchain. Summary of the Invention

[0004] This application provides a method and system for power Internet of Things device identity authentication based on quantum cloud code, which is used to solve the technical problem that traditional authentication technology is difficult to simultaneously ensure the security and scalability of authentication. By combining quantum cryptography with blockchain technology, a highly secure, low-overhead, and scalable device identity authentication mechanism is achieved.

[0005] In the first aspect, the present application provides an identity authentication method for power Internet of Things devices based on quantum cloud code, and the identity authentication method for power Internet of Things devices based on quantum cloud code includes: collecting quantum state information through a photoelectric detector in a quantum random number generator of the power equipment, generating a power authentication seed using a quantum state purification algorithm, and generating a power equipment quantum cloud code initial seed based on a quantum-classical converter; collecting power equipment security identification and power characteristic parameters from the power Internet of Things terminal, and generating a power equipment feature vector through a power equipment feature fusion algorithm; expanding the power equipment quantum cloud code initial seed into a power authentication subkey sequence through a power authentication hash function, performing quantum entangled state encoding based on the power equipment feature vector, and generating a power authentication quantum cloud code through a quantum error correction coding mechanism; establishing a power equipment authentication time window, performing quantum unitary transformation based on the power authentication quantum cloud code, and performing quantum evolution in combination with power environment parameters to generate a power dynamic authentication code; receiving a quantum challenge sequence sent by a power authentication center, performing quantum state measurement according to the power dynamic authentication code, and constructing power authentication response data through a quantum zero-knowledge proof mechanism; establishing an authentication blockchain storage structure for the power authentication response data, and determining the authentication status through an authentication smart contract mechanism.

[0006] In a second aspect, the present application provides a power Internet of Things device identity authentication system based on quantum cloud code, and the power Internet of Things device identity authentication system based on quantum cloud code includes:

[0007] The acquisition module is used to collect quantum state information through the photoelectric detector in the quantum random number generator of the power equipment, generate the power authentication seed using the quantum state purification algorithm, and generate the initial seed of the quantum cloud code of the power equipment based on the quantum-classical converter;

[0008] A fusion module is used to collect power equipment security identification and power characteristic parameters from the power Internet of Things terminal, and generate a power equipment feature vector through a power equipment feature fusion algorithm;

[0009] An expansion module is used to expand the initial seed of the power equipment quantum cloud code into a power authentication subkey sequence through a power authentication hash function, perform quantum entangled state encoding according to the power equipment characteristic vector, and generate a power authentication quantum cloud code through a quantum error correction coding mechanism;

[0010] A transformation module is used to establish a time window for power equipment authentication, perform quantum unitary transformation based on the power authentication quantum cloud code, and perform quantum evolution in combination with power environment parameters to generate a power dynamic authentication code;

[0011] A measurement module is configured to receive a quantum challenge sequence sent by the power authentication center, perform quantum state measurement based on the power dynamic authentication code, and construct power authentication response data via a quantum zero-knowledge proof mechanism;

[0012] The authentication module is used to establish an authentication blockchain storage structure for the power authentication response data and determine the authentication status through an authentication smart contract mechanism.

[0013] The technical solution provided in this application generates true random quantum state information using a quantum random number generator in power equipment, combined with a quantum state purification algorithm to eliminate environmental noise interference, thereby improving the purity and unpredictability of the authentication seed. Unique identification of the device is achieved by collecting the hardware identification and characteristic parameters of the power equipment and generating a feature vector using a feature fusion algorithm. The initial quantum cloud code seed is expanded into a subkey sequence using a power authentication hash function. Quantum entangled state encoding and quantum error correction coding mechanisms are combined to enhance the anti-interference and security of the authentication process. Quantum unitary transformations are performed within a time window based on the power authentication quantum cloud code, and quantum evolution is performed in conjunction with power environment parameters, enabling the authentication process to adapt to dynamic changes in the device's operating environment. By receiving a quantum challenge sequence from the authentication center and combining quantum state measurement with a zero-knowledge proof mechanism, identity verification is completed without leaking authentication information. Finally, a blockchain storage structure and smart contract mechanism are used to record and verify the authentication status, ensuring the immutability and traceability of the authentication process. The entire solution organically combines quantum cryptography, feature recognition, and blockchain technology to ensure authentication security while achieving efficiency and scalability. BRIEF DESCRIPTION OF THE DRAWINGS

[0014] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following briefly introduces the drawings required for describing the embodiments. Obviously, the drawings described below are some embodiments of the present invention. Those skilled in the art can derive other drawings based on these drawings without inventive effort.

[0015] Figure 1 This is a schematic diagram of an embodiment of a method for authenticating the identity of a power Internet of Things device based on quantum cloud code in an embodiment of the present application;

[0016] Figure 2 This is a schematic diagram of an embodiment of the power Internet of Things device identity authentication system based on quantum cloud code in the embodiment of this application. DETAILED DESCRIPTION

[0017] The embodiments of the present application provide a method and system for authenticating the identity of power Internet of Things devices based on quantum cloud codes. The terms "first", "second", "third", "fourth", etc. (if any) in the specification and claims of this application and the above-mentioned drawings are used to distinguish similar objects and are not necessarily used to describe a specific order or sequence. It should be understood that the data used in this way can be interchangeable where appropriate, so that the embodiments described herein can be implemented in an order other than that illustrated or described herein. In addition, the terms "including" or "having" and any variations thereof are intended to cover non-exclusive inclusions. For example, a process, method, system, product or device that includes a series of steps or units is not necessarily limited to those steps or units that are clearly listed, but may include other steps or units that are not clearly listed or that are inherent to these processes, methods, products or devices.

[0018] For ease of understanding, the specific process of the embodiment of the present application is described below. Figure 1 In the embodiment of the present application, an embodiment of the method for authenticating the identity of a power Internet of Things device based on quantum cloud code includes:

[0019] Step S101: Collect quantum state information via the photoelectric detector in the quantum random number generator of the power equipment, generate a power authentication seed using the quantum state purification algorithm, and generate the power equipment quantum cloud code initial seed based on the quantum-classical converter;

[0020] Step S102: collecting power equipment safety identification and power characteristic parameters from the power Internet of Things terminal, and generating a power equipment feature vector through a power equipment feature fusion algorithm;

[0021] Step S103: Expand the initial seed of the power equipment quantum cloud code into a power authentication subkey sequence through the power authentication hash function, perform quantum entangled state encoding based on the power equipment characteristic vector, and generate the power authentication quantum cloud code through the quantum error correction coding mechanism;

[0022] Step S104: Establish a power equipment authentication time window, perform quantum unitary transformation based on the power authentication quantum cloud code, and perform quantum evolution in combination with power environment parameters to generate a power dynamic authentication code;

[0023] Step S105: Receive the quantum challenge sequence sent by the power authentication center, perform quantum state measurement according to the power dynamic authentication code, and construct power authentication response data through the quantum zero-knowledge proof mechanism;

[0024] Step S106: Establish an authentication blockchain storage structure for the power authentication response data, and determine the authentication status through the authentication smart contract mechanism.

[0025] It is understandable that the execution subject of this application can be a power Internet of Things device identity authentication system based on quantum cloud code, or a terminal or server, which is not limited here. The embodiment of this application is explained by taking the server as the execution subject as an example.

[0026] Specifically, quantum state information is generated by a quantum random number generator in power equipment. Specifically, the single-photon source in this generator produces single photons. These photons, after passing through a polarizer, form photon streams with different polarization states. Photodetectors detect and convert these quantum states. The quantum state purification algorithm removes environmental noise interference during the quantum state purification process, ensuring the high purity of the obtained quantum state. The quantum-classical converter converts the purified quantum state into a classical binary sequence, generating the initial seed for the power equipment quantum cloud code. This initial seed is truly random and unpredictable, providing fundamental security for subsequent identity authentication. For power IoT terminal devices, hardware feature information and physical characteristic parameters must be collected. Hardware feature information includes hardware identifiers such as the CPU serial number, MAC address, and IMEI number. Physical characteristic parameters include voltage fluctuations, current fluctuations, and electromagnetic radiation characteristics. The power equipment feature fusion algorithm integrates these features, extracting frequency domain features through wavelet transform. Multi-scale decomposition and principal component analysis are then used for dimensionality reduction to ultimately generate a feature vector that uniquely identifies the device.

[0027] Subsequently, the power authentication hash function expands the initial seed of the power equipment quantum cloud code to generate a series of sub-key sequences. Quantum entangled state encoding encodes the power equipment's characteristic vector into the quantum state. A quantum state rotation algorithm then performs a precise angle rotation on the quantum state to form a unique quantum fingerprint. The quantum error correction coding mechanism uses Shor or Steane codes to correct errors in the quantum cloud code, improving its anti-interference capabilities and ultimately generating the power authentication quantum cloud code.

[0028] During the time window establishment process, a sliding time window is constructed based on the operating cycle of the power equipment, and the quantum cloud code is dynamically transformed within each time window. The quantum unitary transformation continuously evolves the quantum cloud code through the quantum state evolution algorithm. At the same time, the quantum state evolution parameters are dynamically adjusted based on parameters such as the temperature, humidity, and electromagnetic environment of the power equipment to generate a dynamic power authentication code.

[0029] When identity authentication is required, the Power Certification Center sends a quantum challenge sequence to the device. Based on the power dynamic authentication code, the device uses quantum state measurement technology to measure the quantum cloud code and obtain the measurement result. A quantum zero-knowledge proof mechanism ensures that the quantum cloud code itself is not leaked during the authentication process, while also generating power authentication response data. Finally, the power authentication response data is stored in a blockchain structure, and a data hash tree is constructed using the Merkle tree algorithm to ensure that the data cannot be tampered with. The authentication smart contract mechanism uses the PBFT consensus algorithm to verify the block and determine the final authentication status based on pre-set contract rules.

[0030] For example, when a smart terminal device at a power substation performs identity authentication, a quantum random number generator first generates a sequence of quantum states. The raw quantum state information collected by the photodetector is processed using a quantum state purification algorithm, resulting in quantum states with a purity of 99.9%. These quantum states are then converted into a 256-bit initial seed using a quantum-classical converter. Simultaneously, the CPU serial number collected from the terminal device is "CPUID-x86-789012," and the MAC address is "00:1B:44:11:3A:B7." Feature extraction generates a 48-dimensional feature vector. The 256-bit initial seed is expanded into a 1024-bit subkey sequence using a power authentication hash function. This subkey is then quantum-entangled and encoded with the 48-dimensional feature vector to generate a stable quantum cloud code for power authentication. During the 10-minute authentication window, the device environment maintained a temperature of 25°C, a humidity of 45%, and an electromagnetic field strength of 0.8 mT. These parameters are used to adjust the quantum state evolution process. When the authentication center sends a quantum challenge sequence consisting of 20 basis vectors, the device performs quantum state measurements based on the current power dynamic authentication code. The generated authentication response data is secured using a zero-knowledge proof. Ultimately, this data is packaged into a 2MB block and verified using the PBFT consensus algorithm, completing the authentication process. This approach ensures that the authentication scheme maintains exceptional security even in the face of quantum computing threats.

[0031] In this embodiment, a quantum random number generator (QNRG) in a power device generates true random quantum state information, combined with a quantum state purification algorithm to eliminate environmental noise interference, thereby improving the purity and unpredictability of the authentication seed. Unique identification of the device is achieved by collecting the hardware identification and characteristic parameters of the power device and generating a feature vector using a feature fusion algorithm. The initial quantum cloud code seed is expanded into a subkey sequence using a power authentication hash function. Quantum entangled state encoding and quantum error correction coding mechanisms are combined to enhance the anti-interference and security of the authentication process. Quantum unitary transformations are performed within a time window based on the power authentication quantum cloud code, and quantum evolution is performed in conjunction with power environment parameters, enabling the authentication process to adapt to dynamic changes in the device's operating environment. By receiving a quantum challenge sequence from the authentication center and combining quantum state measurement with a zero-knowledge proof mechanism, identity verification is completed without leaking authentication information. Finally, a blockchain storage structure and smart contract mechanism are used to record and verify the authentication status, ensuring the immutability and traceability of the authentication process. The entire solution organically combines quantum cryptography, feature recognition, and blockchain technology, ensuring both authentication security and efficiency and scalability.

[0032] In a specific embodiment, the process of executing step S101 may specifically include the following steps:

[0033] (1) Loading the single-photon source excitation parameters into the quantum random number generator of the power equipment, and generating the initial quantum state sequence through photon polarization modulation;

[0034] (2) Using quantum Bragg grating to compensate the optical path difference of the initial quantum state sequence, and obtaining a steady-state photon flow through quantum phase modulation;

[0035] (3) Setting a photodetection threshold for the steady-state photon flow, sampling the quantum state based on the photodetector, and obtaining the original quantum state information;

[0036] (4) Establish a quantum noise model for the original information of the quantum state, eliminate environmental interference through the quantum state purification algorithm, and generate a pure quantum state;

[0037] (5) Input the pure quantum state into the quantum-classical converter, perform state conversion based on the quantum bit mapping relationship, and obtain the power authentication seed;

[0038] (6) Construct a quantum state mapping matrix based on the power authentication seed, use the quantum state superposition principle to perform state synthesis, and generate the initial seed of the quantum cloud code of the power equipment.

[0039] Specifically, the excitation parameters of a single-photon source are loaded into the quantum random number generator of the power equipment. A single-photon source is a quantum device capable of generating single photons. Its excitation parameters include excitation voltage, pulse width, and repetition rate. The single-photon source is made of quantum dot material and emits single photons triggered by an electrical pulse. When the photons pass through a polarizer, they are modulated into different polarization states according to the principles of quantum mechanics, including horizontal, vertical, and diagonal polarization states, thus forming an initial quantum state sequence. Next, a quantum Bragg grating (QBG) processes this initial quantum state sequence. A QBG is a periodic refractive index modulated structure that precisely controls the transmission path of the photons. By adjusting the grating period and refractive index difference, the optical path difference is compensated, ensuring that the photons maintain coherence during transmission. A quantum phase modulator phase modulates the photons, changing their phase through the electro-optical effect to form a stable photon stream with a defined phase relationship and photon number distribution.

[0040] After obtaining a steady-state photon flow, it is necessary to set an appropriate photodetection threshold. A photodetector is a device that converts optical signals into electrical signals, and its threshold determines its sensitivity to photons. By setting an appropriate detection threshold, background noise can be effectively filtered out, and only true single-photon events can be recorded. During quantum state sampling, the photodetector measures the steady-state photon flow at a preset sampling frequency, recording the arrival time and polarization state of each photon, thereby obtaining the original quantum state information. Establishing a quantum noise model for the collected original quantum state information is crucial. The quantum noise model accounts for the effects of factors such as ambient temperature fluctuations, electromagnetic interference, and detector dark counts on the quantum state. The quantum state purification algorithm eliminates these environmental interferences through quantum state reconstruction and purification operations. Specifically, a density matrix is ​​first constructed to describe the degree of mixing of the quantum state, and then a pure quantum state is reconstructed through quantum state tomography, ultimately obtaining a pure quantum state with high fidelity.

[0041] Inputting the obtained pure quantum state into the quantum-classical converter is a key step in converting quantum states to classical bits. Based on quantum measurement theory, the quantum-classical converter establishes a mapping relationship between quantum bits and classical bits. By selecting an appropriate measurement basis, a projection measurement of the quantum state is performed, collapsing the quantum superposition state into a defined classical state, ultimately generating a power authentication seed. This conversion process must ensure the randomness and unpredictability of the measurement results. The final step is to construct a quantum state mapping matrix using the power authentication seed. This matrix defines how the classical bit sequence is re-encoded into quantum states. Using the principle of quantum state superposition, multiple basis states are linearly combined to create a complex quantum superposition state. This process generates unique quantum state characteristics by controlling the amplitude and phase of each basis state, ultimately forming the initial seed for the quantum cloud code of the power device.

[0042] For example, in an IoT terminal device for a large power transformer, the single-photon source uses InGaAs quantum dots. Under conditions of an excitation voltage of 1.2V and a pulse width of 100ns, it generates single photons with a wavelength of 1550nm. After polarization modulation, an initial quantum state sequence is formed, including horizontal polarization (0°), vertical polarization (90°), and diagonal polarization (45°). The period of the quantum Bragg grating is set to 535nm, with a refractive index difference of 0.01, achieving precise compensation for the optical path difference. The photodetector's dark count rate is set to 100Hz, with a detection efficiency of 85% and a sampling frequency of 1MHz. During the quantum state purification process, the quantum state purity is increased from an initial 92% to 99.5% through density matrix reconstruction. During the quantum-classical conversion process, six orthogonal measurement bases, each containing four measurement operators, are used to generate a 256-bit power authentication seed. This 256-bit seed is converted into a superposition state of 32 qubits using a quantum state mapping matrix. The phase and amplitude of each qubit are precisely controlled, ultimately generating a unique and random initial seed for the power equipment quantum cloud code. The entire process takes only 100ms to complete, meeting the requirements of real-time authentication.

[0043] In a specific embodiment, the process of executing step S102 may specifically include the following steps:

[0044] (1) Collect the CPU serial number, MAC address and IMEI code of the power equipment in the power Internet of Things terminal, and generate the power equipment security identification based on the secure hash algorithm;

[0045] (2) The voltage and current fluctuations of the equipment are measured by the power consumption sensor of the power equipment, and the electromagnetic radiation characteristics are superimposed to form the power characteristic parameters;

[0046] (3) Perform wavelet transform on the power characteristic parameters, construct the power characteristic spectrum, select the characteristic frequency band of the power equipment, and generate the frequency domain characteristics of the power equipment;

[0047] (4) Perform multi-scale decomposition of the power equipment safety identification and the power equipment frequency domain characteristics, and screen out the key parameters of the power characteristics through adaptive feature selection;

[0048] (5) Establish a correlation matrix based on the key parameters of power characteristics, perform dimensionality reduction through principal component analysis algorithm, and construct the principal components of power equipment characteristics;

[0049] (6) Construct a feature mapping relationship for the main components of the power equipment characteristics, integrate the features through a multi-dimensional feature fusion algorithm, and generate a power equipment feature vector.

[0050] Specifically, in the power IoT terminal, the device feature extraction process begins by collecting the device's hardware identification information. This hardware identification includes the CPU serial number (a 48-bit unique identifier), the MAC address (a 48-bit network interface identifier), and the IMEI code (a 15-bit mobile device identifier). These identifiers are processed using the secure hash algorithm SHA-3 to generate a 256-bit secure identifier for the power device, ensuring the uniqueness and unforgeability of this hardware identification information. The power device's power consumption sensor continuously monitors the device's operating status at a sampling frequency of 10kHz, recording voltage fluctuations within ±5% of the rated value and current fluctuations within ±10% of the rated value. Simultaneously, an electromagnetic radiation detector measures the electromagnetic radiation characteristics generated by the device during operation, including electromagnetic field strength and frequency distribution, at a sampling rate of 1MHz. These data are time-synchronized to form a complete sequence of power feature parameters.

[0051] Wavelet transform is applied to the collected power characteristic parameters for time-frequency analysis. The Daubechies wavelet basis function is selected to perform a 5-layer decomposition of the signal to obtain coefficients of different frequency bands. By reconstructing the coefficients of each frequency band, a power characteristic spectrum is constructed to show the frequency distribution characteristics in the range of 0-500kHz. According to the typical working characteristics of the equipment, the 100-200kHz frequency band is selected as the characteristic frequency band to generate the frequency domain characteristics of the power equipment. The power equipment safety identification and the power equipment frequency domain characteristics are processed by a multi-scale decomposition algorithm, and wavelet packets of different scales are used to decompose to obtain feature representations at multiple scale levels. The adaptive feature selection algorithm calculates the importance score of each feature based on the information gain criterion and selects the feature combination with the highest score as the key power characteristic parameter.

[0052] The correlation matrix R is calculated for the key parameters of power characteristics. The matrix element calculation formula is:

[0053]

[0054] in: represents the correlation coefficient between the i-th feature and the j-th feature, represents the i-th eigenvalue of the k-th sample, represents the j-th eigenvalue of the k-th sample, represents the mean of the i-th feature, represents the mean of the jth feature, represents the standard deviation of the i-th feature, represents the standard deviation of the j-th feature, represents the weight coefficient of the kth feature, represents the time decay factor, and n represents the number of samples.

[0055] The correlation matrix was decomposed using the principal component analysis algorithm. Eigenvectors with a cumulative contribution rate of 95% were selected as principal components to construct the power equipment characteristic principal components. Finally, a multidimensional feature fusion algorithm was used to integrate the principal components through a weighted combination to generate the final power equipment characteristic vector.

[0056] For example, the feature extraction process for a smart power distribution terminal device is as follows: First, the CPU serial number "INTEL-i5-7500U-89457", MAC address "00:1A:2B:3C:4D:5E", and IMEI code "490154203237518" are obtained and processed using the SHA-3 algorithm to obtain a 256-bit security identifier. The power consumption sensor records voltage fluctuation data at a sampling rate of 10kHz over 10 minutes. The rated voltage is 220V, but the actual fluctuation range is 209V-231V. The current fluctuation data is rated at 5A, but the actual fluctuation range is 4.5A-5.5A. Electromagnetic radiation signature measurements reveal significant characteristic harmonics in the 100-200kHz frequency band. After wavelet transform decomposition, device-specific operating harmonics are detected in the 150kHz frequency band, with an amplitude 1.2 times the standard operating level. Multi-scale decomposition yields 16 feature parameters, from which the eight highest-scoring parameters are selected using an adaptive feature selection algorithm. These eight characteristic parameters were calculated through principal component analysis, with the cumulative contribution of the first four principal components reaching 96.7%. The resulting power equipment feature vector had 128 dimensions, with each dimension ranging from -1 to 1. This provided standardized input data for the subsequent quantum encoding process. The data processing time for the entire feature extraction process was less than 200ms, meeting the performance requirements for real-time authentication.

[0057] In a specific embodiment, the process of executing step S103 may specifically include the following steps:

[0058] (1) Input the initial seed of the quantum cloud code of the power equipment into the power authentication hash function, construct the hash transformation matrix through the quantum bit mapping relationship, and generate the power authentication basic key;

[0059] (2) Construct a quantum key expansion network based on the basic key of power authentication, perform key expansion transformation through quantum permutation algorithm, and form a power authentication subkey sequence;

[0060] (3) Establish a quantum state preparation circuit for the characteristic vector of the power equipment, encode the characteristic data into quantum states through quantum gate operations, and obtain the quantum characteristic state;

[0061] (4) Entangling the quantum characteristic state with the power authentication sub-key sequence, constructing entanglement correlation based on Bell state measurement, and generating an entangled quantum state;

[0062] (5) Perform Shor quantum error correction coding on the entangled quantum state, determine the error location through quantum comprehensive measurement, and form a steady-state quantum code;

[0063] (6) A quantum state reconstruction matrix is ​​established for the steady-state quantum code, and the state is integrated through the quantum state fusion algorithm to generate the power authentication quantum cloud code.

[0064] Specifically, during the quantum cloud code generation process, the initial seed of the power equipment quantum cloud code is first input into the power authentication hash function. This hash function is based on an improved SHA-3 algorithm and uses quantum bit mapping relationships to construct a hash transformation matrix. Each classical bit is mapped to the quantum state space, and a hash operation is performed to generate the power authentication base key. This base key consists of 256 quantum bits, each of which is maintained in a quantum superposition state. Based on the generated power authentication base key, a quantum key expansion network is constructed. This network uses a quantum permutation algorithm to achieve key expansion transformation through control gate operations. During the key expansion process, each base key bit undergoes a combination of quantum gates such as Hadamard gates and CNOT gates to form a longer power authentication subkey sequence. The expanded subkey sequence reaches a length of 1024 bits, maintaining the quantum properties of the original key.

[0065] A quantum state preparation circuit is established for the characteristic vector of the power device. This circuit consists of multiple quantum gates. The characteristic data is encoded using single-qubit rotation gates (X, Y, and Z gates) and two-qubit control gates (CNOT and SWAP gates). Each characteristic component is encoded onto its corresponding qubit, ultimately forming a quantum characteristic state that reflects the device's characteristics. The quantum characteristic state is then entangled with the power authentication subkey sequence, and an entangled correlation is established using Bell state measurement. Bell state measurement projects paired qubits onto a maximally entangled state, ensuring a strong correlation between the quantum characteristic state and the key sequence, generating a stable entangled quantum state.

[0066] Shor quantum error correction encoding of entangled quantum states is a key step in ensuring the stability of quantum information. The Shor code encoding formula is:

[0067]

[0068] in: represents the encoded quantum state, represents the amplitude coefficient of the i-th ground state, represents the generator of quantum error correction code, and represents the auxiliary qubit state, represents the error correction strength parameter, n represents the dimension of the coding space, and m represents the distance of the error correction code.

[0069] After determining the error location through quantum comprehensive measurement, a steady-state quantum code is formed. The final step is to establish a quantum state reconstruction matrix for the steady-state quantum code. Using a quantum state fusion algorithm, multiple quantum states are superimposed and combined to generate the final quantum cloud code for power authentication.

[0070] For example, during the authentication process for a high-voltage distribution device, a 256-bit quantum cloud code initial seed is received and processed using a power authentication hash function to generate a power authentication base key. This base key is expanded through a quantum key expansion network, with every 4 qubits being expanded to 16 qubits, ultimately forming a 1024-bit subkey sequence. The power device's characteristic vector contains 128 characteristic components, each encoded onto a corresponding qubit, forming a quantum eigenstate. Subsequently, the 1024-bit subkey sequence is Bell-entangled with the 128-bit quantum eigenstate, and the entangled state is constructed through a combination of CNOT gates and Hadamard gates. The resulting entangled quantum state is encoded using a [[9,1,3]] Shor code, which encodes one logical bit using 9 physical bits. This code is capable of correcting any single-bit error. A quantum state fusion algorithm ultimately combines these encoded quantum states into a 2048-bit power authentication quantum cloud code. The entire process is processed within 50 microseconds, meeting real-time authentication requirements.

[0071] In a specific embodiment, the process of executing step S104 may specifically include the following steps:

[0072] (1) Based on the working cycle of the power equipment, a time sliding window is constructed, and the quantum state evolution interval is determined by the quantum timing analysis algorithm to generate the power equipment authentication time window;

[0073] (2) Establish a quantum unitary operator matrix for the power authentication quantum cloud code, perform quantum state transformation through the Schrödinger evolution equation, and form a quantum transformation sequence;

[0074] (3) Collect temperature, humidity and electromagnetic environment data of power equipment, construct an environmental feature matrix through environmental parameter analysis algorithm, and generate power environment parameters;

[0075] (4) Perform quantum state interference between the quantum transformation sequence and the power environment parameters, construct a correlation matrix through the quantum entangled state evolution algorithm, and form a dynamic quantum state;

[0076] (5) Calculate the quantum density matrix for the dynamic quantum state, perform quantum state evolution through the quantum state reconstruction algorithm, and obtain the certified dynamic sequence;

[0077] (6) The authentication dynamic sequence is subjected to quantum bit rearrangement through a quantum state mapping circuit, and a power dynamic authentication code is generated through a quantum state fusion algorithm.

[0078] Specifically, its operating characteristics are analyzed to construct a time sliding window. The working cycle of power equipment includes stages such as startup, stable operation, fluctuation, and dormancy, and each stage has different quantum state evolution characteristics. The quantum timing analysis algorithm determines the optimal quantum state evolution interval by observing the change law of the quantum state at different time points. This interval needs to cover the key working states of the equipment while ensuring the continuity and stability of the quantum state, and finally generate the power equipment authentication time window. Within the generated time window, a quantum unitary operator matrix is ​​established for the power authentication quantum cloud code. The quantum unitary operator is a basic tool for describing the evolution of the quantum state, and the quantum state is accurately transformed through the Schrödinger evolution equation. This transformation process maintains the normalization and coherence of the quantum state, maps the original quantum cloud code to the new quantum state space, and forms a quantum transformation sequence.

[0079] As the quantum state evolves, environmental parameters of the power equipment need to be collected. Temperature sensors monitor changes in the equipment's operating temperature in real time, humidity sensors record fluctuations in ambient humidity, and electromagnetic field detectors measure the strength of the surrounding electromagnetic environment. An environmental parameter analysis algorithm normalizes this data, constructs an environmental characteristic matrix, and generates standardized power environmental parameters. The quantum transformation sequence is combined with the power environmental parameters through a quantum state interference process, and the quantum entangled state evolution algorithm creates a quantum correlation between the two. This correlation ensures that the authentication process can adapt to environmental changes. By constructing a correlation matrix to record the interaction between the quantum state and environmental parameters, a dynamic quantum state is ultimately formed.

[0080] For the dynamic quantum state formed, calculate its quantum density matrix. The calculation formula of the quantum density matrix is:

[0081]

[0082] in: represents the quantum density matrix at time t, represents the coherence term coefficient between quantum states, and represents the quantum ground state, represents the decoherence coefficient, The quantum state energy difference, represents the coherence time, and N represents the dimension of the quantum system.

[0083] The density matrix is ​​evolved using a quantum state reconstruction algorithm to obtain an authentication dynamic sequence that reflects the real-time status of the device. Finally, the authentication dynamic sequence is input into a quantum state mapping circuit, where the final power dynamic authentication code is generated through quantum bit rearrangement and quantum state fusion algorithms.

[0084] For example, during dynamic authentication, a smart meter operates on a 15-minute cycle. Quantum timing analysis determined the optimal evolution interval to be 3 minutes. Within this time window, the power authentication quantum cloud code undergoes a quantum unitary transformation, updating its state every 0.1 seconds. Simultaneously, environmental monitoring indicates that the device's operating temperature rises from 25°C to 35°C, the relative humidity remains at 45%, and the ambient electromagnetic field intensity is 0.5 mT. These environmental parameters are converted into a 12×12 environmental characteristic matrix. After quantum state interference, a 32-qubit dynamic quantum state containing environmental information is formed. Quantum density matrix calculations show that quantum coherence remains above 98% during the 3-minute evolution process. The resulting 256-bit power dynamic authentication code incorporates multi-dimensional information, including device identity, environmental characteristics, and a timestamp. The computational latency of the entire dynamic authentication process is kept within 10 milliseconds.

[0085] In a specific embodiment, the process of executing step S105 may specifically include the following steps:

[0086] (1) Establish a quantum communication channel with the power certification center, receive quantum entangled state pairs, and extract the quantum challenge sequence through the quantum channel analysis algorithm;

[0087] (2) Perform quantum state superposition on the quantum challenge sequence and the power dynamic authentication code, construct a quantum measurement basis through the quantum state interference algorithm, and form a quantum measurement matrix;

[0088] (3) Calculate the projection operator for the quantum measurement matrix, determine the quantum state probability distribution through quantum state projection measurement, and generate the quantum measurement result;

[0089] (4) Construct a zero-knowledge proof protocol for the quantum measurement results, construct a proof circuit using the Groth16 algorithm, and obtain zero-knowledge proof data;

[0090] (5) Associate and map the zero-knowledge proof data with the quantum measurement results, and generate an authentication proof sequence through the zero-knowledge verification algorithm;

[0091] (6) A quantum state reconstruction matrix is ​​established for the authentication proof sequence, and data is integrated through the quantum state fusion algorithm to generate power authentication response data.

[0092] Specifically, a quantum communication channel must first be established between the power IoT device and the authentication center. This channel utilizes quantum key distribution technology to ensure secure communication. During the channel establishment process, the authentication center generates a pair of entangled photons, transmits one photon to the device via quantum optical fiber, and retains the other photon. The quantum channel resolution algorithm determines the quantum state of the entangled photons through Bell state measurements and extracts a quantum challenge sequence containing random basis vectors. Once the quantum challenge sequence is obtained, it is quantum-superimposed with the power dynamic authentication code. The quantum state interference algorithm utilizes the quantum interference effect to coherently superimpose the two sets of quantum states in different basis vector spaces. By adjusting the phase relationship, a complete quantum measurement basis is constructed. This process forms a quantum measurement matrix that contains complete information about the measurement basis.

[0093] For the constructed quantum measurement matrix, the corresponding projection operator is calculated. Quantum state projection measurement projects the quantum state onto a specific measurement basis to obtain the probability distribution of the measurement result. The projection operation collapses the quantum state by selecting an appropriate measurement direction to obtain the classical measurement result. This process records the probability of each measurement result, forming a complete quantum measurement result dataset. Next, a zero-knowledge proof protocol is constructed for the quantum measurement results. The Groth16 algorithm is an efficient zero-knowledge proof algorithm that proves the validity of the measurement result by constructing a circuit. The algorithm first converts the measurement result into an arithmetic circuit, then generates the prover's witness data and the verifier's verification data, ultimately forming a compact zero-knowledge proof data.

[0094] The generated zero-knowledge proof data is mapped to the quantum measurement results. The zero-knowledge verification algorithm verifies the validity of the proof data, ensuring that the quantum measurement results have not been tampered with while also preserving the specific information of the original measurement data. This process generates an authentication proof sequence containing the proof information. The final step is to establish a quantum state reconstruction matrix for the authentication proof sequence. The quantum state fusion algorithm integrates the components of the proof sequence to reconstruct the complete quantum state information and generate the final power authentication response data. This response data contains both the quantum measurement results and the verification information of the zero-knowledge proof.

[0095] For example, when a smart terminal device in a power distribution room performs identity authentication, it first receives entangled photons sent by the authentication center via a quantum communication channel. The photons have a wavelength of 1550 nm, and their polarization states include horizontal, vertical, diagonal, and anti-diagonal. A quantum channel analysis algorithm measures the polarization states of the photons using a photon detector, generating a quantum challenge sequence consisting of 32 orthogonal basis vectors. These basis vectors are quantum-superimposed with a 256-bit power dynamic authentication code to form an 8×8 quantum measurement matrix. During the projection measurement process, each quantum state is repeatedly measured 1000 times, and the frequency of occurrence of each measurement result is recorded to obtain the measurement probability distribution. The Groth16 algorithm converts this measurement data into a circuit format, generating 384-byte zero-knowledge proof data. This proof data is then mapped with the original measurement results to generate a 512-bit authentication proof sequence. Finally, the quantum state fusion algorithm integrates this data into a 1024-bit power authentication response. The entire authentication process takes only 25 milliseconds to compute, maintaining the confidentiality of the authentication information.

[0096] In a specific embodiment, the process of executing step S106 may specifically include the following steps:

[0097] (1) Group the power authentication response data according to timestamps, construct a data hash tree using the Merkle tree algorithm, and generate authentication block data;

[0098] (2) Establish a consensus node network for authentication block data, perform block verification through the PBFT consensus algorithm, and form an authentication blockchain structure;

[0099] (3) Extract the transaction data from the authentication blockchain structure, convert it into bytecode through the smart contract compiler, and construct the authentication smart contract;

[0100] (4) Assign permissions to the authentication smart contract, establish contract call rules through the role access control algorithm, and generate a contract access matrix;

[0101] (5) Analyze the authentication log based on the contract access matrix, verify the authentication rules through the state machine transition algorithm, and form an authentication state vector;

[0102] (6) The authentication state vector is confirmed through a multi-signature algorithm, and the authentication state is generated through the blockchain consensus mechanism.

[0103] Specifically, the power authentication response data is first grouped by timestamp, with each group containing authentication data within a fixed time window. The Merkle tree algorithm organizes this data into a binary hash tree structure, with leaf nodes storing the hash value of the original data, and non-leaf nodes storing the combined hash of their child nodes' hash values. This structure allows for rapid verification of data integrity. Any data modification results in a change in the root hash value, generating verifiable authentication block data. Once the block data is generated, a consensus node network is established for verification. The PBFT (Practical Byzantine Fault Tolerance) consensus algorithm ensures consistency among nodes in the network through a three-phase commit protocol. Each node first performs a pre-prepare phase to verify the format and signature of the block data. Next, in the prepare phase, nodes exchange verification results. Finally, in the commit phase, all nodes reach consensus on the block's validity, forming the final authenticated blockchain structure.

[0104] Transaction data is extracted from the established authentication blockchain structure, containing a complete record of device authentication. A smart contract compiler converts contract code written in a high-level language into bytecode executable by the Ethereum Virtual Machine (EVM). The compilation process includes syntax analysis, semantic checking, optimization, and target code generation, ultimately constructing an authentication smart contract used to verify device identity. Permission management for the authentication smart contract is implemented through a role-based access control algorithm. This algorithm defines permission levels for different roles (such as device, verifier, and administrator) and sets the set of contract functions that each role can call. This generates a contract access matrix, in which each element represents the access rights granted to a specific role to a specific function.

[0105] Based on the generated contract access matrix, the log data generated during the authentication process is analyzed. The state machine transition algorithm abstracts the authentication process into a series of state transitions, each corresponding to a different stage of device authentication. By verifying the legitimacy of state transitions, the authentication process is ensured to comply with the preset rules, ultimately forming a state vector reflecting the authentication results.

[0106] Finally, a multi-signature algorithm is used to confirm the authentication state vector. This algorithm requires multiple authorized nodes to sign the state. Only when a sufficient number of valid signatures are collected can the final authentication state be determined through the blockchain consensus mechanism.

[0107] For example, during the authentication process of a smart power distribution device, authentication response data received every five minutes is organized into a data block, generating a total of 12 data blocks. A Merkle tree algorithm hashes these blocks, generating a binary tree with a depth of four and a root node hash value of 256 bits. In a network consisting of seven consensus nodes, the PBFT algorithm requires consensus among at least five nodes for authentication to succeed. After authentication, transaction data is extracted and compiled into bytecode. The resulting smart contract includes functions such as device authentication, status query, and permission management. The contract's access control matrix defines three roles: device node (which can call authentication functions), verification node (which can call verification functions), and management node (which can call management functions). The state machine defines four states: unauthenticated, authenticating, successful, and failed. Analysis of one day's authentication logs revealed 1,440 authentication requests, of which 1,438 transitioned to valid states, while two requests were marked as abnormal due to timeouts. The final authentication state vector is multi-signed by 5 authorized nodes, each signature uses a 2048-bit RSA key, and the complete signature verification process takes no more than 100 milliseconds.

[0108] The above describes the power Internet of Things device identity authentication method based on quantum cloud code in the embodiment of the present application. The following describes the power Internet of Things device identity authentication system based on quantum cloud code in the embodiment of the present application. Please refer to Figure 2 In the embodiment of the present application, an embodiment of the power Internet of Things device identity authentication system based on quantum cloud code includes:

[0109] The acquisition module is used to collect quantum state information through the photoelectric detector in the quantum random number generator of the power equipment, generate the power authentication seed using the quantum state purification algorithm, and generate the initial seed of the quantum cloud code of the power equipment based on the quantum-classical converter;

[0110] A fusion module is used to collect power equipment security identification and power characteristic parameters from the power Internet of Things terminal, and generate a power equipment feature vector through a power equipment feature fusion algorithm;

[0111] An expansion module is used to expand the initial seed of the power equipment quantum cloud code into a power authentication subkey sequence through a power authentication hash function, perform quantum entangled state encoding according to the power equipment characteristic vector, and generate a power authentication quantum cloud code through a quantum error correction coding mechanism;

[0112] A transformation module is used to establish a time window for power equipment authentication, perform quantum unitary transformation based on the power authentication quantum cloud code, and perform quantum evolution in combination with power environment parameters to generate a power dynamic authentication code;

[0113] A measurement module is configured to receive a quantum challenge sequence sent by the power authentication center, perform quantum state measurement based on the power dynamic authentication code, and construct power authentication response data via a quantum zero-knowledge proof mechanism;

[0114] The authentication module is used to establish an authentication blockchain storage structure for the power authentication response data and determine the authentication status through an authentication smart contract mechanism.

[0115] Through the collaborative efforts of the aforementioned components, the power equipment's quantum random number generator generates true random quantum state information, which, combined with a quantum state purification algorithm to eliminate environmental noise interference, improves the purity and unpredictability of the authentication seed. Unique identification of the device is achieved by collecting the hardware identification and characteristic parameters of the power equipment and generating a feature vector using a feature fusion algorithm. The initial quantum cloud code seed is expanded into a subkey sequence using a power authentication hash function. Quantum entangled state encoding and quantum error correction coding mechanisms are combined to enhance the authentication process's robustness and security. Quantum unitary transformations are performed within a time window based on the power authentication quantum cloud code, and quantum evolution is performed based on power environment parameters, enabling the authentication process to adapt to dynamic changes in the device's operating environment. By receiving a quantum challenge sequence from the authentication center and combining quantum state measurement with a zero-knowledge proof mechanism, identity verification is completed without leaking authentication information. Finally, a blockchain storage structure and smart contract mechanism are used to record and verify the authentication status, ensuring the immutability and traceability of the authentication process. The entire solution organically combines quantum cryptography, feature recognition, and blockchain technology, ensuring both security and efficiency and scalability.

[0116] As described above, the above embodiments are only used to illustrate the technical solutions of the present application, rather than to limit them. Although the present application has been described in detail with reference to the above embodiments, those skilled in the art should understand that they can still modify the technical solutions described in the above embodiments, or make equivalent replacements for some of the technical features therein. However, these modifications or replacements do not deviate the essence of the corresponding technical solutions from the spirit and scope of the technical solutions of the embodiments of the present application.

Claims

1. A method for authenticating the identity of power Internet of Things devices based on quantum cloud code, characterized in that: The power Internet of Things device identity authentication method based on quantum cloud code includes: The quantum state information is collected through the photoelectric detector in the quantum random number generator of the power equipment, and the power authentication seed is generated using the quantum state purification algorithm. The initial seed of the quantum cloud code of the power equipment is generated based on the quantum-classical converter; Collect power equipment safety identification and power characteristic parameters from the power Internet of Things terminal, and generate power equipment feature vectors through the power equipment feature fusion algorithm; Expanding the initial seed of the power equipment quantum cloud code into a power authentication subkey sequence through a power authentication hash function, performing quantum entangled state encoding according to the power equipment feature vector, and generating a power authentication quantum cloud code through a quantum error correction coding mechanism; Establishing a time window for power equipment authentication, performing quantum unitary transformation based on the power authentication quantum cloud code, and performing quantum evolution in combination with power environment parameters to generate a power dynamic authentication code; Receive the quantum challenge sequence sent by the power authentication center, perform quantum state measurement according to the power dynamic authentication code, and construct power authentication response data through the quantum zero-knowledge proof mechanism; Establishing an authentication blockchain storage structure for the power authentication response data, and determining the authentication status through an authentication smart contract mechanism; The method collects quantum state information via a photoelectric detector in a quantum random number generator of a power device, generates a power authentication seed using a quantum state purification algorithm, and generates a quantum cloud code initial seed for the power device based on a quantum-classical converter, including: Loading single-photon source excitation parameters into the quantum random number generator of the power equipment, generating the initial quantum state sequence through photon polarization modulation; The quantum Bragg grating is used to compensate the optical path difference of the initial quantum state sequence and a steady-state photon flow is obtained through quantum phase modulation. Setting a photoelectric detection threshold for the steady-state photon flow, performing quantum state sampling based on a photoelectric detector, and obtaining original quantum state information; A quantum noise model is established for the original information of the quantum state, and environmental interference is eliminated through a quantum state purification algorithm to generate a pure quantum state; Inputting the pure quantum state into a quantum-classical converter, performing state conversion based on a quantum bit mapping relationship, and obtaining a power authentication seed; Constructing a quantum state mapping matrix based on the power authentication seed, using the quantum state superposition principle to perform state synthesis, and generating the initial seed of the quantum cloud code for the power equipment; The method includes: expanding the initial seed of the power equipment quantum cloud code into a power authentication subkey sequence through a power authentication hash function, performing quantum entangled state encoding according to the power equipment characteristic vector, and generating a power authentication quantum cloud code through a quantum error correction coding mechanism, including: Input the initial seed of the quantum cloud code of the power equipment into the power authentication hash function, construct a hash transformation matrix through the quantum bit mapping relationship, and generate the power authentication basic key; Constructing a quantum key expansion network based on the power authentication basic key, performing key expansion transformation through a quantum permutation algorithm to form a power authentication sub-key sequence; Establishing a quantum state preparation circuit for the characteristic vector of the power equipment, performing quantum state encoding on the characteristic data through quantum gate operation to obtain a quantum characteristic state; Entangling the quantum characteristic state with the power authentication sub-key sequence, constructing an entangled association based on Bell state measurement, and generating an entangled quantum state; Performing Shor quantum error correction coding on the entangled quantum state, determining the error position through quantum comprehensive measurement, and forming a steady-state quantum code; A quantum state reconstruction matrix is ​​established for the steady-state quantum code, and state integration is performed through a quantum state fusion algorithm to generate a power authentication quantum cloud code.

2. The method for authenticating the identity of an electric power Internet of Things device based on quantum cloud code according to claim 1 is characterized in that: The method of collecting power equipment safety identification and power characteristic parameters from the power Internet of Things terminal and generating a power equipment feature vector through a power equipment feature fusion algorithm includes: Collect the CPU serial number, MAC address and IMEI code of the power equipment in the power Internet of Things terminal, and generate the power equipment security identification based on the secure hash algorithm; The power consumption sensor of the power equipment measures the voltage and current fluctuations of the equipment, superimposes the electromagnetic radiation characteristics, and forms the power characteristic parameters; Performing wavelet transform on the power characteristic parameters, constructing a power characteristic spectrum diagram, selecting a characteristic frequency band of the power equipment, and generating a frequency domain characteristic of the power equipment; Performing multi-scale decomposition on the power equipment safety identification and the power equipment frequency domain characteristics, and screening out key power characteristic parameters through adaptive feature selection; Establishing a correlation matrix based on the key parameters of the power characteristics, performing dimensionality reduction using a principal component analysis algorithm, and constructing the principal components of the power equipment characteristics; A feature mapping relationship is constructed for the main components of the power equipment characteristics, and feature integration is performed through a multi-dimensional feature fusion algorithm to generate a power equipment feature vector.

3. The method for authenticating the identity of power Internet of Things devices based on quantum cloud code according to claim 1 is characterized in that: The step of establishing a power equipment authentication time window, performing quantum unitary transformation based on the power authentication quantum cloud code, and performing quantum evolution in combination with power environment parameters to generate a power dynamic authentication code includes: A time sliding window is constructed based on the working cycle of the power equipment, and the quantum state evolution interval is determined through the quantum timing analysis algorithm to generate the power equipment authentication time window; A quantum unitary operator matrix is ​​established for the power authentication quantum cloud code, and a quantum state transformation is performed through the Schrödinger evolution equation to form a quantum transformation sequence; Collect temperature, humidity and electromagnetic environment data of power equipment, build an environmental feature matrix through environmental parameter analysis algorithm, and generate power environment parameters; Performing quantum state interference on the quantum transformation sequence and the power environment parameter, constructing a correlation matrix through a quantum entangled state evolution algorithm, and forming a dynamic quantum state; Calculating a quantum density matrix for the dynamic quantum state, performing quantum state evolution using a quantum state reconstruction algorithm, and obtaining an authenticated dynamic sequence; The authentication dynamic sequence is subjected to quantum bit rearrangement via a quantum state mapping circuit, and a power dynamic authentication code is generated through a quantum state fusion algorithm.

4. The method for authenticating the identity of an electric power Internet of Things device based on quantum cloud code according to claim 1 is characterized in that: The receiving quantum challenge sequence sent by the power authentication center, performing quantum state measurement according to the power dynamic authentication code, and constructing power authentication response data via a quantum zero-knowledge proof mechanism include: Establish a quantum communication channel with the power certification center, receive quantum entangled state pairs, and extract the quantum challenge sequence through the quantum channel analysis algorithm; Perform quantum state superposition of the quantum challenge sequence and the power dynamic authentication code, construct a quantum measurement basis through a quantum state interference algorithm, and form a quantum measurement matrix; Calculating a projection operator for the quantum measurement matrix, determining a quantum state probability distribution through quantum state projection measurement, and generating a quantum measurement result; Constructing a zero-knowledge proof protocol for the quantum measurement result, constructing a proof circuit using the Groth16 algorithm, and obtaining zero-knowledge proof data; Associating and mapping the zero-knowledge proof data with the quantum measurement result, and generating an authentication proof sequence through a zero-knowledge verification algorithm; A quantum state reconstruction matrix is ​​established for the authentication proof sequence, and data is integrated through a quantum state fusion algorithm to generate power authentication response data.

5. The method for authenticating the identity of an electric power Internet of Things device based on quantum cloud code according to claim 4 is characterized in that: The step of establishing an authentication blockchain storage structure for the power authentication response data and determining the authentication status through an authentication smart contract mechanism includes: The power authentication response data is grouped according to timestamps, a data hash tree is constructed using a Merkle tree algorithm, and authentication block data is generated; Establish a consensus node network for the authentication block data, perform block verification through the PBFT consensus algorithm, and form an authentication blockchain structure; Extracting transaction data from the authentication blockchain structure, converting it into bytecode using a smart contract compiler, and constructing an authentication smart contract; Assign permissions to the authentication smart contract, establish contract call rules through role-based access control algorithm, and generate a contract access matrix; Analyze the authentication log based on the contract access matrix, verify the authentication rules through the state machine transition algorithm, and form an authentication state vector; The authentication state vector is confirmed through a multi-signature algorithm, and the authentication state is generated through a blockchain consensus mechanism.

6. A power Internet of Things device identity authentication system based on quantum cloud code, used to implement the power Internet of Things device identity authentication method based on quantum cloud code as described in any one of claims 1 to 5, characterized in that: The power Internet of Things device identity authentication system based on quantum cloud code includes: The acquisition module is used to collect quantum state information through the photoelectric detector in the quantum random number generator of the power equipment, generate the power authentication seed using the quantum state purification algorithm, and generate the initial seed of the quantum cloud code of the power equipment based on the quantum-classical converter; A fusion module is used to collect power equipment security identification and power characteristic parameters from the power Internet of Things terminal, and generate a power equipment feature vector through a power equipment feature fusion algorithm; An expansion module is used to expand the initial seed of the power equipment quantum cloud code into a power authentication subkey sequence through a power authentication hash function, perform quantum entangled state encoding according to the power equipment characteristic vector, and generate a power authentication quantum cloud code through a quantum error correction coding mechanism; A transformation module is used to establish a time window for power equipment authentication, perform quantum unitary transformation based on the power authentication quantum cloud code, and perform quantum evolution in combination with power environment parameters to generate a power dynamic authentication code; A measurement module is configured to receive a quantum challenge sequence sent by the power authentication center, perform quantum state measurement based on the power dynamic authentication code, and construct power authentication response data via a quantum zero-knowledge proof mechanism; The authentication module is used to establish an authentication blockchain storage structure for the power authentication response data and determine the authentication status through an authentication smart contract mechanism.

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