Multi-node secure communication method and system based on quantum key distribution

Abstract

The invention discloses a multi-node secure communication method and system based on quantum key distribution, and the method comprises the steps: evaluating multi-dimensional parameters of a quantum channel, dynamically updating a node reputation value, constructing a four-dimensional topological graph database, and generating candidate routing paths based on a Monte Carlo tree search algorithm; a state-action space is constructed by further combining reinforcement learning, and path selection is optimized by using a dual Q network and a priority experience playback mechanism; through multi-dimensional channel assessment and node reputation value dynamic updating, the defects of a traditional quantum network static routing strategy are overcome, the communication safety and efficiency are improved, and low-delay and high-reliability key distribution of a complex quantum network is supported.

Description

Technical Field

[0001] The present invention relates to the field of communication security technologies, and in particular, to a multi-node secure communication method and system based on quantum key distribution. Background Art

[0002] With the rapid development of quantum communication technologies, quantum key distribution (QKD) has shown great application potential in ensuring communication security due to its security based on the principles of quantum mechanics. In recent years, quantum key distribution technologies have gradually evolved from the initial point-to-point communication mode to a multi-node networked communication mode to meet broader practical application requirements. However, in a multi-node quantum communication network, the increase in the number of nodes and the complexity of the network topology make the quality assessment of quantum channels, the dynamic construction of network topologies, and the efficient selection of secure routes become key issues that need to be urgently solved. Existing quantum key distribution networks usually adopt static or simple dynamic routing strategies, lacking multi-dimensional refined assessment of channel quality, and it is difficult to effectively cope with the dynamic changes in quantum channel quality and the real-time fluctuations in node reputation, resulting in the overall security and communication efficiency of the network being difficult to be effectively guaranteed.

[0003] Specifically, existing technologies often only focus on a single indicator in the assessment of quantum channel quality, while ignoring the comprehensive impact of multi-dimensional factors, making it difficult to accurately reflect the real-time state of the channel. In addition, existing technologies lack a dynamic update mechanism for the reputation values of network nodes, and are unable to identify and isolate nodes with declining reputation or potential malicious nodes in a timely manner, resulting in an increase in network security risks. Moreover, traditional routing selection methods mostly adopt simple shortest path or fixed weight algorithms, and fail to fully consider the dynamic changes in network topology and the real-time update of node reputation values, making it difficult to quickly and accurately determine the optimal secure communication path in a complex network environment.

[0004] Therefore, how to achieve multi-dimensional refined assessment of quantum channel quality, real-time dynamic update of node reputation values, and efficient optimization of secure routing paths has become an important technical problem that needs to be urgently solved in the field of multi-node secure communication based on quantum key distribution. Summary of the Invention

[0005] The purpose of this part is to outline some aspects of the embodiments of the present invention and briefly introduce some preferred embodiments. Some simplifications or omissions may be made in this part, as well as in the abstract and title of the present application, to avoid obscuring the purpose of this part, the abstract, and the title, and such simplifications or omissions shall not be used to limit the scope of the present invention.

[0006] In view of the above existing problems, the present invention is proposed. Therefore, the present invention provides a multi-node secure communication method based on quantum key distribution to solve the problems mentioned in the background art.

[0007] To solve the above technical problems, the present invention provides the following technical solutions:

[0008] In a first aspect, the present invention provides a multi-node secure communication method based on quantum key distribution, including:

[0009] Evaluating the quality of the quantum channel, generating a multi-dimensional channel quality parameter set, and updating the reputation values of each node in the network through the multi-dimensional channel quality parameter set;

[0010] According to the updated reputation values of each node in the network and the multi-dimensional channel quality parameter set, constructing a topological graph database of the network, and using the constructed topological graph database as input, applying the Monte Carlo tree search algorithm to generate candidate routing paths;

[0011] Optimizing the generated candidate routing paths and combining the real-time network status to select the final routing path, ensuring the security of quantum key distribution in multi-node communication.

[0012] As a preferred solution of the multi-node secure communication method based on quantum key distribution according to the present invention, wherein: the multi-dimensional channel quality parameter set includes:

[0013] Photon transmission efficiency, link stability, and dynamic change of quantum bit error rate;

[0014] Calculating the basic attenuation of the quantum channel through the logarithm ratio, and combining the additional attenuation caused by external environmental perturbations to obtain the photon transmission efficiency;

[0015] Constructing a stability factor through the transmission delay and the quantum bit error rate, and evaluating the link stability with the stability factor;

[0016] Evaluating the dynamic change of the quantum bit error rate through the dynamic weight of the quantum bit error rate.

[0017] As a preferred solution of the multi-node secure communication method based on quantum key distribution according to the present invention, wherein: updating the reputation values of each node in the network through the multi-dimensional channel quality parameter set includes:

[0018] Updating the reputation value based on the relay success rate and online stability of the nodes in the network;

[0019] Generating a reputation value interval through preset high and low thresholds. When the reputation value is less than the minimum value of the reputation value interval, the reputation verification protocol is triggered;

[0020] When the reputation value is greater than the maximum value of the reputation value interval, the fast election channel is activated.

[0021] As a preferred solution of the multi-node secure communication method based on quantum key distribution according to the present invention, wherein: a topological graph database of the network is constructed, including:

[0022] The topological graph database is constructed by periodically sending entangled photon pulse sequences and synchronous detection frames;

[0023] The topological graph database is stored as a four-dimensional graph structure, and the four-dimensional graph structure includes a node set, an edge set, weights, and time stamps, and the weights are obtained based on the dynamic change of the quantum bit error rate and the photon transmission efficiency.

[0024] As a preferred solution of the multi-node secure communication method based on quantum key distribution according to the present invention, wherein: taking the constructed topological graph database as an input, the Monte Carlo tree search algorithm is applied to generate candidate routing paths, including:

[0025] Through the Monte Carlo tree search algorithm, the node state of the search tree is defined, and the node state is represented as the path cumulative cost and the remaining potential value;

[0026] By performing weighted summation on the weights of each edge in the topological graph database and considering the relationship between the edge weight and the number of hops, the path cumulative cost is obtained;

[0027] By calculating the minimum value of the node reputation value and the link stability, the remaining potential value is obtained.

[0028] As a preferred solution of the multi-node secure communication method based on quantum key distribution according to the present invention, wherein: optimizing the generated candidate routing paths, including:

[0029] Reinforcement learning is adopted to construct a state-action space;

[0030] The state space is composed of the current node identifier, the remaining number of hops, the minimum reputation value of the nodes in the path, and the maximum quantum bit error rate weight of the links in the path;

[0031] The action space is composed of direct connection relay, cross-layer relay, and emergency channel activation.

[0032] As a preferred solution of the multi-node secure communication method based on quantum key distribution according to the present invention, wherein: further including:

[0033] The reinforcement learning adopts a double Q-network update mechanism and prioritized experience replay;

[0034] The double Q-network is a main network and a target network, and the prioritized experience replay determines the sampling probability based on the temporal difference error.

[0035] Second aspect, the present invention provides a multi-node secure communication system based on quantum key distribution, which includes:

[0036] A channel quality evaluation and reputation update module, configured to evaluate the quality of the quantum channel, generate a multi-dimensional channel quality parameter set, and update the reputation values of each node in the network through the multi-dimensional channel quality parameter set;

[0037] A topology modeling and routing planning module, configured to construct a topology graph database of the network according to the updated reputation values of each node in the network and the multi-dimensional channel quality parameter set, and use the constructed topology graph database as an input to apply the Monte Carlo tree search algorithm to generate candidate routing paths;

[0038] A path optimization module, configured to optimize the generated candidate routing paths and select the final routing path in combination with the real-time network state, ensuring the security of quantum key distribution in multi-node communication.

[0039] Third aspect, the present invention provides a computer device, including a memory and a processor, where the memory stores a computer program, and: when the processor executes the computer program, any step of the above method is implemented.

[0040] Fourth aspect, the present invention provides a computer-readable storage medium, on which a computer program is stored, and: when the computer program is executed by a processor, any step of the above method is implemented.

[0041] Compared with the prior art, the beneficial effects of the invention are:

[0042] 1. By comprehensively evaluating the dynamic changes of photon transmission efficiency, link stability, and bit error rate, a multi-dimensional parameter set is constructed, solving the limitations of traditional single-index analysis; in addition, by combining the dynamic weight of the quantum bit error rate and the compensation for external environmental disturbances, the real-time performance and stability of channel quality analysis can be improved, providing refined data support for routing decisions;

[0043] 2. By constructing a four-dimensional dynamic topology graph and generating routing candidate paths in combination with the Monte Carlo tree search algorithm; it can achieve the rapid convergence of the globally optimal path in a complex network environment, improving routing efficiency; at the same time, the introduction of reinforcement learning can respond to network fluctuations in real time, reduce communication delays, ensure low-bit-error-rate transmission, and achieve the efficiency and security of the quantum key distribution network. Description of the Drawings

[0044] To more clearly illustrate the technical solutions of the embodiments of the present invention, the following will briefly introduce the accompanying drawings required for the description of the embodiments. Obviously, the accompanying drawings in the following description are only some embodiments of the present invention. For those of ordinary skill in the art, without creative efforts, other accompanying drawings can also be obtained based on these drawings. Among them:

[0045] Figure 1 It is the overall flowchart of the multi-node secure communication method based on quantum key distribution according to an embodiment of the present invention. Specific embodiments

[0046] To make the above objects, features, and advantages of the present invention more obvious and understandable, the following will describe the specific embodiments of the present invention in detail with reference to the accompanying drawings of the specification. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of them. Based on the embodiments of the present invention, all other embodiments obtained by those of ordinary skill in the art without creative efforts shall fall within the protection scope of the present invention.

[0047] In the following description, many specific details are set forth to facilitate a full understanding of the present invention. However, the present invention can also be implemented in other ways different from those described herein. Those skilled in the art can make similar extensions without departing from the connotation of the present invention. Therefore, the present invention is not limited by the specific embodiments disclosed below.

[0048] Secondly, the so-called "one embodiment" or "embodiment" herein refers to a specific feature, structure, or characteristic that can be included in at least one implementation manner of the present invention. The "in one embodiment" that appears in different places in this specification does not necessarily refer to the same embodiment, nor is it a separate or alternative embodiment that mutually excludes other embodiments.

[0049] The present invention is described in detail in conjunction with schematic diagrams. When detailing the embodiments of the present invention, for the convenience of explanation, the cross-sectional views showing the device structure will be enlarged locally not in accordance with the general scale, and the schematic diagrams are only examples and should not limit the protection scope of the present invention here. In addition, in actual production, three-dimensional spatial dimensions including length, width, and depth should be included.

[0050] At the same time, in the description of the present invention, it should be noted that the orientation or positional relationships indicated by terms such as "upper, lower, inner, and outer" are based on the orientation or positional relationships shown in the accompanying drawings. It is only for the convenience of describing the present invention and simplifying the description, rather than indicating or implying that the device or element referred to must have a specific orientation, be constructed and operated in a specific orientation, and therefore cannot be understood as a limitation to the present invention. In addition, the terms "first, second, or third" are only used for descriptive purposes and cannot be understood as indicating or implying relative importance.

[0051] Unless otherwise clearly specified and defined in the present invention, the terms "installation, connection, and coupling" shall be understood in a broad sense. For example, it can be a fixed connection, a detachable connection, or an integral connection; it can also be a mechanical connection, an electrical connection, or a direct connection, or it can be indirectly connected through an intermediate medium, or it can be the communication inside two components. For those of ordinary skill in the art, the specific meanings of the above terms in the present invention can be understood according to specific circumstances.

[0052] Embodiment 1

[0053] Referring to Figure 1 , which is the first embodiment of the present invention. This embodiment provides a multi-node secure communication method based on quantum key distribution, including:

[0054] S1. Evaluate the quality of the quantum channel, generate a multi-dimensional channel quality parameter set, and update the reputation values of each node in the network through the multi-dimensional channel quality parameter set;

[0055] It should be noted that evaluating the quality of the quantum channel is an important step to ensure the security and reliability of the quantum key distribution (QKD) network. Therefore, it is necessary to comprehensively evaluate the quantum channel through multi-dimensional parameters;

[0056] Specifically, the multi-dimensional parameters use the photon transmission efficiency, link stability, and dynamic change of the quantum bit error rate as the evaluation indicators of the quantum channel quality;

[0057] Specifically, the channel loss is measured by the photon transmission efficiency, which reflects the loss degree of photons during the transmission process;

[0058] Furthermore, at the sending end, a high-precision power meter is used to measure the power at the sending end, and at the receiving end, a single-photon detector is used to measure the power at the receiving end. The basic attenuation of the quantum channel is calculated through the logarithmic ratio, and considering the additional attenuation caused by external environmental disturbances (such as temperature, vibration, and electromagnetic interference), the basic attenuation and the additional attenuation are added together to obtain the time-varying channel attenuation coefficient;

[0059] Specifically, the time-varying channel attenuation coefficient can effectively reflect the photon transmission efficiency. The time-varying channel attenuation coefficient α(t) is expressed by the formula:

[0060]

[0061] where P t represents the power at the sending end, P r represents the power at the receiving end, represents the basic attenuation, Δα(θ) represents the additional attenuation; t represents time;

[0062] It should be noted that, different from traditional communication methods, the transmitting end is the source of signals, responsible for generating and sending signals. In quantum communication, it is usually a photon source for generating single photons or entangled photon pairs. Its communication process is as follows: the quantum information (quantum bits) carried by photons is transmitted through a quantum channel (such as an optical fiber or free space) to the receiving end by the transmitting end; while the receiving end is the signal receiving point, responsible for detecting and decoding the signals sent by the transmitting end. In quantum communication, it is usually equipped with a single-photon detector for detecting the arriving photons and extracting the quantum information (quantum bits) therein; that is to say, the transmitting end refers to the node that sends quantum signals (photons), and the receiving end refers to the node that receives and measures quantum signals; by comparing the measurement results of the transmitting end and the receiving end, a shared key, namely the quantum key, is generated.

[0063] Specifically, the link stability reflects the reliability of the channel during long-term operation, which also includes the transmission delay and the quantum bit error rate. The quantum bit error rate is obtained from the quantum information transmitted in quantum communication and is used to measure the error rate of qubit transmission.

[0064] Furthermore, the transmitting end embeds the sending time into the frame to form a timestamped probe frame, and then sends it to the receiving end. After receiving the probe frame, the receiving end reads the timestamped probe frame and compares it with the receiving time of the receiving end to calculate the time required for the probe frame to be transmitted in the network, thereby obtaining the transmission delay of the measurement network.

[0065] It should be noted that the probe frame is a special network data packet used to test the performance or status of the network. It usually carries specific information to help the receiving end analyze network characteristics, such as delay or packet loss rate, etc.

[0066] Even further, a stability factor is constructed based on the transmission delay and the quantum bit error rate.

[0067] Specifically, the formula for the stability factor is expressed as follows:

[0068]

[0069] where Δt represents the transmission delay, μ Δt represents the mean value of the delay, represents the variance of the delay, ρ QBER,Δt represents the correlation coefficient between the quantum bit error rate (Quantum Bit Error Rate, QBER) and its transmission delay Δt; l represents the stability factor. If the stability factor is closer to 1, it indicates that the link is more stable.

[0070] It should be noted that to obtain the dynamic change of the quantum bit error rate, it is necessary not only to monitor and collect QBER data in real time, but also to define the critical threshold and slope factor of the quantum bit error rate through experiments; in QKD, the critical threshold of the quantum bit error rate refers to the maximum bit error rate allowed in the quantum channel. If it exceeds this value, it is considered that there is eavesdropping (Eve) in the channel, and then the security of quantum key distribution cannot be guaranteed; the slope factor refers to the attenuation rate of the secure key rate with distance (or channel loss), which reflects the robustness of the system to channel loss and noise. That is to say, the slope factor determines the maximum secure distance of quantum key distribution; here, the scheme of the present invention defines the dynamic weight of the quantum bit error rate through the critical threshold and slope factor of the quantum bit error rate to reflect the dynamic change of the quantum bit error rate, where for the dynamic weight QBER of the quantum bit error rate w , it is defined as follows:

[0071]

[0072] where Q th is the critical threshold of the quantum bit error rate, and k is the slope factor of the quantum bit error rate;

[0073] It should be noted that since the reputation value of a node reflects the reliability and performance of the node in the network, by quantifying the reflected photon transmission efficiency, link stability, and quantum bit error rate into specific values and using them as the basis for updating the reputation value of the node, the dynamic adjustment of the reputation values of each node in the network can be realized. This method can more accurately reflect the real-time performance of the node and ensure the reliability and security of the nodes in the network;

[0074] Furthermore, in addition to the reflected photon transmission efficiency, link stability, and quantum bit error rate, the update of the reputation value of the node is also based on the relay success rate and online stability of the nodes in the network, and is obtained as follows:

[0075]

[0076] where R i (t) represents the reputation value of the i-th node, λ is the forgetting factor, and its function is to represent the weights of the historical reputation value and the current reputation value. T c represents the online stability, and C s represents the relay success rate;

[0077] It should be noted that the relay success rate includes the reflected photon transmission efficiency, link stability, and quantum bit error rate, because the evaluation of the channel quality directly affects the relay success rate of the nodes in the network;

[0078] Further, by presetting high and low thresholds to generate a reputation value range, when the reputation value is less than the minimum value of the reputation value range, a reputation verification protocol is triggered;

[0079] It should be noted that the preset high and low thresholds are set by the expert experience method, and the values are the upper and lower limits of the interval range. The purpose is to judge the reliability of the node; when the reputation value is less than the minimum value of the reputation value range, it means that the node is unreliable and needs additional verification; when the reputation value is greater than the maximum value of the reputation value range, it means that the node is very reliable, so there is no need for verification and it can directly participate in network decision-making or resource allocation;

[0080] Specifically, the reputation verification protocol is a security protocol used to audit and verify a node when its reputation value is abnormal. This protocol can adopt the Shamir secret sharing or Byzantine fault tolerance algorithm;

[0081] Further, when the reputation value is greater than the maximum value of the reputation value range, a fast election channel is activated;

[0082] Specifically, the fast election channel is an optimized network decision-making mechanism that allows high-reputation nodes to directly participate in important decisions or resource allocation in the network. That is to say, high-reputation nodes can preferentially become relay nodes to optimize the communication path, thereby improving the overall performance of the network;

[0083] S2. According to the reputation values of each node in the updated network and the multi-dimensional channel quality parameter set, construct a topological graph database of the network. Using the constructed topological graph database as input, apply the Monte Carlo tree search algorithm to generate candidate routing paths;

[0084] It should be noted that since quantum key distribution (QKD) depends on the quality of the quantum channel to be secure, and in a multi-node network, the connection relationship between nodes is dynamically changing, a method is needed to monitor and record these changes in real time;

[0085] Further, by periodically sending entangled photon pulse sequences and synchronous detection frames, a topological graph database is constructed;

[0086] It should be noted that the entangled photon pulse sequence is used to detect the channel state in real time, and the synchronous detection frame contains a time stamp and a topology discovery code, which is used to ensure the uniqueness of the information in the topological graph database;

[0087] Further, the topological graph database is stored as a four-dimensional graph structure, and the four-dimensional graph structure includes a node set, an edge set, weights, and time stamps;

[0088] Specifically, the constructed topological graph database G can be expressed as:

[0089] G(V, E, W, T)

[0090] Among them, V represents the set of nodes of the network, E represents the set of edges formed by the nodes of the network, that is, the edge set, W represents the weight of the edges in the network, and T represents the time stamp, which is used to record the timeliness of the information in the topological graph database;

[0091] Specifically, the weight is obtained based on the dynamic change of the quantum bit error rate and the photon transmission efficiency:

[0092] W = QBER w (i, j) × α(t)

[0093] Among them, (i, j) represents the edge between node i and node j;

[0094] Specifically, if the network is undirected, then QBER w (i, j) = QBER w (j, i), otherwise QBER w (i, j) ≠ QBER w (j, i);

[0095] It should be noted that in a multi-node quantum communication network, due to the characteristics of the topological graph database, its topological structure may change at any time. If traditional shortest path or fixed weight algorithms are used, they can often only make limited adjustments in static or simple dynamic scenarios and it is difficult to take into account the real-time update of multi-dimensional parameters; in addition, the search tree and simulation data of MCTS can provide rich prior information and preliminary strategies for the reinforcement learning algorithm, making the reinforcement learning converge faster and have better effects on the network;

[0096] Furthermore, through the Monte Carlo tree search algorithm, the node state of the search tree is defined, candidate paths are generated, and the path with the minimum total cost is selected for key distribution;

[0097] Specifically, the node state is represented as the path cumulative cost and the remaining potential value;

[0098] Even further, by performing a weighted sum of the weights of each edge in the topological graph database and considering the relationship between the edge weight and the number of hops, the path cumulative cost is obtained;

[0099] Specifically, the path cumulative cost C(s) is calculated by the following formula:

[0100]

[0101] Among them, W g is the weight of edge g, Δd represents the hop count increment, d maxis denoted as the maximum allowed hop count; path represents the candidate path that the current Monte Carlo Tree Search (MCTS) is evaluating (i.e., the sequence of paths from the source node to the current node);

[0102] It should be noted that the hop count increment represents the increase in the total path hop count when the path is extended from the current node to the next node (usually 1); for example, if the current path already contains 3 hops (i.e., passes through 3 relay nodes), then after extending to the next node, the hop count increment is 1 and the total hop count becomes 4; the maximum allowed hop count is mainly used to limit the maximum length of the quantum communication path (i.e., the maximum number of relay nodes passed through); because for each additional hop, operations such as quantum state storage and entanglement swapping at the relay node need to be experienced, which will lead to the accumulation of transmission delay, and for each relay node passed through, the quantum bit error rate may increase due to operation errors. When the number of hops is more, the end-to-end (transmitter to receiver) bit error rate is higher, so the maximum allowed hop count must be restricted;

[0103] Furthermore, by calculating the minimum value of the reputation value of the node and the link stability, the remaining potential value is obtained;

[0104] Specifically, the remaining potential value V(s) is calculated by the following formula:

[0105]

[0106] where v represents the candidate node in the network topology;

[0107] It should be noted that when the Monte Carlo tree search generates a routing path, the algorithm needs to expand from the end node of the current path (such as node C) to adjacent nodes (such as D, E, F). For example, if the adjacent node D is not in the current path (A→B→C) (i.e., ), then it is allowed to expand to A→B→C→D. If the adjacent node B is already in the current path (i.e., B∈path), then it is prohibited to expand to A→B→C→B (forming a loop); thus, it shows that the design can ensure that the candidate path does not pass through the same node repeatedly and prevent the formation of a loop; in addition, since the explored nodes have been restricted, the search space of the algorithm is further reduced, which improves the efficiency of the Monte Carlo tree search algorithm indirectly;

[0108] S3. Optimize the generated candidate routing path and select the final routing path in combination with the real-time network state, ensuring the security of quantum key distribution in multi-node communication;

[0109] Furthermore, reinforcement learning is adopted to construct a state-action space without considering the reward factor;

[0110] Furthermore, the state space consists of the current node identifier, the remaining number of hops, the minimum reputation value of the nodes in the path, and the maximum quantum bit error rate weight of the links in the path;

[0111] Specifically, the remaining number of hops is obtained by subtracting the number of hops already taken from the maximum allowed number of hops from the current node to the target node;

[0112] Specifically, the current node identifier is obtained by one-hot encoding;

[0113] Furthermore, the action space consists of direct relay, cross-layer relay, and emergency channel activation;

[0114] Specifically, direct relay is defined as selecting the next-hop relay node directly connected to the current node;

[0115] It should be noted that if the current node has only two adjacent nodes and both have joined the routing path, the direct relay action is blocked, and cross-layer or emergency channel is forced to be selected;

[0116] Specifically, cross-layer relay is defined as skipping intermediate nodes and connecting to non-adjacent but directly reachable nodes;

[0117] It should be noted that emergency channel activation is to enable backup links (such as satellite relay or high-redundancy optical fiber), and the cost is relatively high. In non-essential cases, it is set to the non-trigger state;

[0118] Further, the reinforcement learning adopts a double Q-network update mechanism and prioritized experience replay;

[0119] Specifically, the double Q-network consists of a main network and a target network. The prioritized experience replay determines the sampling probability based on the temporal difference error;

[0120] It should be noted that the main network updates the state in real time and is used to select the action space. The target network synchronizes the main network parameters periodically and is used to calculate the target Q value;

[0121] Specifically, the double Q-network update mechanism is parameter delay synchronization, that is, the weights of the main network are copied to the weights of the target network every N steps. The loss function L(θ) of the main network is expressed as:

[0122]

[0123] Among them, θ represents the main network, Q(s,a;θ) represents the Q-value prediction of the main network for action a in state s; y represents the target Q value;

[0124] Specifically, the prioritized experience replay sets the priority according to the temporal difference error:

[0125] δ = |y - Q(s, a; θ)|

[0126] Among them, δ represents the gap between the current Q-value prediction and the target value. The larger the error, the higher the priority;

[0127] Specifically, the sampling probability H(i) is determined by the following formula:

[0128]

[0129] Among them, β represents the priority strength coefficient. When taking 0, it is uniform sampling, and when taking 1, it is priority sampling; p i represents the priority;

[0130] It should be noted that by binding the action space of reinforcement learning with the physical constraints of the quantum network (routing path, node reputation value, and quantum bit error rate), the ineffective exploration in the routing path is avoided, enabling the rapid and accurate determination of the optimal secure communication path in a complex network environment.

[0131] Furthermore, this embodiment also provides a multi-node secure communication system based on quantum key distribution, including:

[0132] A channel quality evaluation and reputation update module, configured to evaluate the quality of the quantum channel, generate a multi-dimensional channel quality parameter set, and update the reputation values of each node in the network through the multi-dimensional channel quality parameter set;

[0133] A topology modeling and routing planning module, configured to construct a topology graph database of the network according to the updated reputation values of each node in the network and the multi-dimensional channel quality parameter set, and use the constructed topology graph database as an input to apply the Monte Carlo tree search algorithm to generate candidate routing paths;

[0134] A path optimization module, configured to optimize the generated candidate routing paths and select the final routing path in combination with the real-time network status, ensuring the security of quantum key distribution in multi-node communication.

[0135] This embodiment also provides a computer device, applicable to the situation of the multi-node secure communication method based on quantum key distribution, including:

[0136] A memory and a processor; the memory is used to store computer-executable instructions, and the processor is used to execute the computer-executable instructions to implement the multi-node secure communication method based on quantum key distribution as proposed in the above embodiment.

[0137] The computer device may be a terminal, which includes a processor, a memory, a communication interface, a display screen, and an input device connected via a system bus. Among them, the processor of the computer device is used to provide computing and control capabilities. The memory of the computer device includes a non-volatile storage medium and an internal memory. The non-volatile storage medium stores an operating system and computer programs. The internal memory provides an environment for the operation of the operating system and computer programs in the non-volatile storage medium. The communication interface of the computer device is used to communicate with an external terminal in a wired or wireless manner, and the wireless manner can be achieved through WIFI, a carrier network, NFC (Near Field Communication), or other technologies. The display screen of the computer device can be a liquid crystal display screen or an electronic ink display screen, and the input device of the computer device can be a touch layer covering the display screen, or a button, a trackball, or a touchpad provided on the housing of the computer device, or an external keyboard, touchpad, or mouse, etc.

[0138] This embodiment also provides a storage medium, on which a computer program is stored, and when the program is executed by a processor, it implements the multi-node secure communication method based on quantum key distribution proposed in the above embodiment.

[0139] The storage medium proposed in this embodiment and the data storage method proposed in the above embodiment belong to the same inventive concept. For technical details not described in detail in this embodiment, reference can be made to the above embodiment, and this embodiment has the same beneficial effects as the above embodiment.

[0140] Those skilled in the art should understand that the embodiments of the present invention can be provided as a method, a system, or a computer program product. Therefore, the present application can adopt the form of a complete hardware embodiment, a complete software embodiment, or an embodiment combining software and hardware aspects. Moreover, the present application can adopt the form of a computer program product implemented on one or more computer-usable storage media (including but not limited to disk memories, CD-ROMs, optical memories, etc.) containing computer-usable program codes. The solutions in the embodiments of the present application can be implemented in various computer languages, for example, object-oriented programming languages such as Java and interpreted scripting languages such as JavaScript.

[0141] This application is described with reference to the flowcharts and / or block diagrams of methods, devices (systems), and computer program products according to the embodiments of the present application. It should be understood that each flow and / or block in the flowchart and / or block diagram can be implemented by computer program instructions, and the combination of the flows and / or blocks in the flowchart and / or block diagram can also be implemented by computer program instructions. These computer program instructions can be provided to the processor of a general-purpose computer, a special-purpose computer, an embedded processor, or other programmable data processing devices to generate a machine, so that the instructions executed by the processor of the computer or other programmable data processing devices generate for implementation in the processFigure 1 means for the functions specified in one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0142] These computer program instructions can also be stored in a computer-readable memory that can direct a computer or other programmable data processing device to work in a specific manner, so that the instructions stored in the computer-readable memory produce a manufactured article including an instruction means that implements the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0143] These computer program instructions can also be loaded onto a computer or other programmable data processing device, so that a series of operation steps are executed on the computer or other programmable device to generate a computer-implemented process. Thus, the instructions executed on the computer or other programmable device provide steps for implementing the functions specified in Figure 1 one process or multiple processes and / or blocks Figure 1 or multiple blocks.

[0144] Although the preferred embodiments of the present application have been described, those skilled in the art can make additional changes and modifications once they know the basic creative concepts. Therefore, the appended claims are intended to be construed to include the preferred embodiments as well as all changes and modifications that fall within the scope of the present application.

[0145] Obviously, those skilled in the art can make various changes and variations to the present application without departing from the spirit and scope of the present application. Thus, if these modifications and variations of the present application fall within the scope of the claims of the present application and their equivalent technologies, the present application also intends to include these modifications and variations.

Claims

1. A multi-node secure communication method based on quantum key distribution, characterized in that: include: Evaluate the quality of the quantum channel, generate a multi-dimensional channel quality parameter set, and update the reputation value of each node in the network through the multi-dimensional channel quality parameter set; Constructing a network topology database according to the updated reputation value of each node in the network and the multi-dimensional channel quality parameter set, and using the constructed topology database as input to generate candidate routing paths by applying a Monte Carlo tree search algorithm; The generated candidate routing paths are optimized, and the final routing path is selected in combination with the real-time network status, thereby ensuring the security of quantum key distribution in multi-node communications.

2. The multi-node secure communication method based on quantum key distribution as claimed in claim 1, characterized in that: The multi-dimensional channel quality parameter set includes: Dynamic changes in photon transmission efficiency, link stability, and quantum bit error rate; The photon transmission efficiency is obtained by calculating the basic attenuation of the quantum channel through the logarithmic ratio and combining the additional attenuation caused by the external environment disturbance; A stability factor is constructed by using the transmission delay and the quantum bit error rate, and the link stability is evaluated by using the stability factor; The dynamic change of the quantum bit error rate is evaluated by the quantum bit error rate dynamic weight.

3. The multi-node secure communication method based on quantum key distribution as claimed in claim 2, characterized in that: Updating the reputation value of each node in the network through the multi-dimensional channel quality parameter set includes: Based on the relay success rate and online stability of the nodes in the network, the reputation value is updated; By presetting high and low thresholds, a reputation value interval is generated, and when the reputation value is less than the minimum value of the reputation value interval, the reputation verification protocol is triggered; When the reputation value is greater than the maximum value of the reputation value interval, the fast election channel is activated.

4. The multi-node secure communication method based on quantum key distribution according to claim 1 or 2, characterized in that: Build a network topology database, including: By periodically sending entangled photon pulse sequences and synchronous detection frames, a topological map database is constructed; The topological graph database is stored as a four-dimensional graph structure, which includes a node set, an edge set, a weight, and a time tag, wherein the weight is obtained based on the dynamic change of quantum bit error rate and photon transmission efficiency.

5. The multi-node secure communication method based on quantum key distribution as claimed in claim 4, characterized in that: The constructed topology database is used as input, and a Monte Carlo tree search algorithm is applied to generate candidate routing paths, including: By using a Monte Carlo tree search algorithm, defining the node state of the search tree, wherein the node state is represented by the path cumulative cost and the remaining potential value; The path cumulative cost is obtained by performing weighted summation on the weight of each edge in the topology database and considering the relationship between the edge weight and the number of hops; The remaining potential value is obtained by calculating the minimum value of the node's reputation value and the link stability.

6. The multi-node secure communication method based on quantum key distribution as claimed in claim 5, characterized in that: Optimizing the generated candidate routing path includes: Use reinforcement learning to construct the state-action space; The state space is composed of the current node identifier, the remaining number of hops, the minimum reputation value of the nodes in the path, and the maximum quantum bit error rate weight of the links in the path; The action space consists of direct relay, cross-layer relay and emergency channel activation.

7. The multi-node secure communication method based on quantum key distribution as claimed in claim 6, characterized in that: Also includes: The reinforcement learning adopts a dual Q network update mechanism and priority experience replay; The dual Q network is a main network and a target network, and the priority experience playback is based on the temporal difference error to determine the sampling probability.

8. A multi-node secure communication system based on quantum key distribution, based on the multi-node secure communication method based on quantum key distribution according to any one of claims 1 to 7, characterized in that: include: A channel quality assessment and reputation update module is configured to assess the quality of the quantum channel, generate a multi-dimensional channel quality parameter set, and update the reputation value of each node in the network through the multi-dimensional channel quality parameter set; A topology modeling and routing planning module is configured to construct a network topology map database according to the updated reputation value of each node in the network and the multi-dimensional channel quality parameter set, and use the constructed topology map database as input to generate candidate routing paths by applying a Monte Carlo tree search algorithm; The path optimization module is configured to optimize the generated candidate routing paths and select the final routing path in combination with the real-time network status, thereby ensuring the security of quantum key distribution in multi-node communication.

9. A computer device comprising a memory and a processor, wherein the memory stores a computer program, wherein: When the processor executes the computer program, the steps of the method according to any one of claims 1 to 7 are implemented.

10. A computer-readable storage medium having a computer program stored thereon, characterized in that: When the computer program is executed by a processor, the steps of the method according to any one of claims 1 to 7 are implemented.

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