Satellite secure transmission optimization method and system based on joint anomaly detection

Abstract

The invention discloses a satellite secure transmission optimization method and system based on joint anomaly detection, mainly solving the problem of low end-to-end transmission reliability under the condition of network attack in the prior art, and the implementation scheme comprises the following steps: constructing a time-varying network topology according to constellation configuration; periodically updating a network topology and a satellite neighbor node set according to the law of satellite orbital motion; the network is monitored in real time based on an anomaly detection mechanism, whether the current network is subjected to interference attack and DoS attack is judged in time, and whether the current satellite can safely transmit data is judged; and according to indexes such as node states, link hops, detection precision, node load capacity and link transmission delay, and according to a network topology and a neighbor node set at the current moment, determining a routing control optimization problem, and guiding each satellite to select an optimal transfer satellite along a transmission direction according to an optimal solution to obtain an end-to-end optimal transmission path. The method can actively trigger a detection mechanism to quickly identify abnormal nodes, obtains a safe and reliable end-to-end transmission path, and can be used for a low earth orbit satellite network.

Description

Technical Field

[0001] The present invention belongs to the field of satellite network technology, and in particular relates to a satellite security transmission optimization method and system, which can be used in low-orbit satellite networks. Background Art

[0002] Satellite networks are a crucial component of next-generation communications networks, featuring flexible network topologies and high-speed interconnect links, enabling ubiquitous high-speed internet services. However, they are also susceptible to network threats such as signal interference, communication interruptions, and eavesdropping and hijacking. Consequently, the deployment of detection mechanisms within these systems has become widely adopted in wireless networks, smart grids, and sensor networks. Typical detection mechanisms estimate attack probabilities based on Bayesian probability and identify anomalous behavior. However, anomaly detection can only detect known attacks and has limitations in detecting unknown ones. Furthermore, the time lag between triggering the detection mechanism and successfully detecting the attack makes current anomaly detection mechanisms incapable of providing real-time defenses for the system. On the other hand, control theory, a classical mathematical theory, leverages control inputs to solve real-time system optimization problems. It is widely used in various scenarios, including highway ramp merging, intersection traffic signal control, drone combat, and air-to-ground attacks.

[0003] A typical network routing mechanism can be divided into four phases: topology extraction, route calculation, route forwarding, and route maintenance. The route forwarding phase, also known as the end-to-end data transmission phase, dynamically selects a transmission path for data packets by comprehensively considering factors such as link status, transmission requirements, and risk. The issue of secure data transmission is becoming increasingly serious, and a wealth of research has been conducted in ad hoc networks, satellite networks, and various other scenarios. This work distinguishes between legitimate and malicious nodes by setting node trust values, selecting trusted nodes as next hops, and guiding data packets along secure paths under certain attack levels. Common trust value calculation models are based on node status and forwarding behavior. However, when a network is under severe attack, the proportion of faulty nodes increases, making it impossible to provide secure end-to-end transmission services based solely on node trust values. Therefore, existing secure transmission algorithms cannot guarantee secure data transmission under various attacks.

[0004] Deploying detection mechanisms within systems has become a solution for improving system robustness and has been widely adopted in wireless networks, smart grids, and sensor networks. Typical detection mechanisms estimate attack probabilities based on Bayesian probability and identify anomalous behavior. However, anomaly detection can only detect known attacks and has limitations in detecting unknown ones. Furthermore, there is a time lag between triggering the detection mechanism and successfully detecting the attack, making current anomaly detection mechanisms unable to provide real-time defense for the system. On the other hand, control theory, a classical mathematical theory that leverages control inputs to solve real-time system optimization problems, is widely used in scenarios such as highway ramp merging, intersection traffic signal control, drone dogfights, and air-to-ground attacks. To address attacks that hinder information exchange between controllers and actuators in cyber-physical systems (CPSs), an active attack detection scheme based on optimal control is proposed. This scheme improves detection performance by designing control inputs. Therefore, combined detection and control has become a new approach to ensuring system security.

[0005] Based on the above analysis, the existing technology faces a pressing technical challenge: Common trust value calculation models are based on node status and forwarding behavior. However, when a network is severely attacked, the proportion of faulty nodes increases, and relying solely on node trust values ​​is insufficient to provide secure end-to-end transmission services. Consequently, existing secure transmission algorithms cannot guarantee secure data transmission under various attacks.

[0006] Patent document CN201510112475.4 discloses a multi-layer satellite network optimal service distribution routing solution based on latency minimization. This solution constructs a low-orbit satellite routing table based on logical regions and virtual node numbers according to the multi-layer satellite communication network architecture and stores it on medium-orbit satellites. Upon arrival of a service, the solution determines whether to forward the service to a low-orbit satellite or to a higher-level satellite based on minimized end-to-end latency, thereby improving the performance of the multi-layer satellite communication network. However, this method increases the burden on each satellite because it involves storing and updating routing tables. Furthermore, because it does not account for attacks within the satellite network, it cannot provide a robust optimal end-to-end latency routing solution for the satellite communication network when interference and DoS attacks affect satellite nodes within the satellite network, and cannot guarantee secure data transmission under various attacks. Summary of the Invention

[0007] The purpose of the present invention is to address the deficiencies of the above-mentioned existing technologies and provide a satellite security transmission optimization method and system based on joint anomaly detection, so as to provide the satellite communication network with optimal end-to-end delay routing that meets robustness, avoid the impact on satellite nodes when the network is subjected to interference attacks and DoS attacks, and ensure the secure transmission of data under various attacks.

[0008] The technical solution for achieving the purpose of the present invention includes:

[0009] 1. A satellite secure transmission optimization method based on joint anomaly detection, characterized by comprising:

[0010] S1) Based on the constellation configuration, the connection relationship between the satellite and its adjacent satellites is clarified, the set of neighbor nodes of the satellite is determined, and a time-varying network topology describing the satellite network is constructed;

[0011] S2) periodically updating the network topology and the satellite's neighbor node set according to the satellite's periodic motion along the orbit;

[0012] S3) Based on the anomaly detection mechanism, the network status is monitored in real time to promptly determine whether the current network is subject to interference attacks and DoS attacks, periodically update the node status including transmission status and security status, and determine whether the current satellite can transmit data safely;

[0013] S4) determining a routing control optimization problem that satisfies system robustness and routing optimal performance based on the current network topology and the constructed neighbor node set, based on link selection indicators such as node status, link hop count, detection accuracy, node load, and link transmission delay, and based on the needs of the source and destination satellites;

[0014] S5) Calculate the optimization problem to obtain the optimal solution, and guide each satellite to select the best relay satellite that can safely transmit from the set of neighboring nodes along the transmission direction according to the optimal solution, so as to obtain the end-to-end optimal transmission path in the current network topology.

[0015] Furthermore, in S4), a routing control optimization problem that satisfies system robustness and routing optimal performance is determined, and its implementation includes the following:

[0016] S41) According to satellite s i The load and node function of satellite s i Processing delay and queuing delay

[0017] S42) According to satellite s i With ground station g i Position and data packet size, calculate the transmission delay of the satellite-to-ground link

[0018] S43) Calculate the propagation delay of the satellite-to-ground link based on the length of the satellite-to-ground link and the medium transmission speed

[0019] S44) Select the next hop neighbor satellite s j , and calculate satellite s based on the packet size i With satellites j Transmission delay

[0020] S45) Calculate the satellite s according to the length of the intersatellite link and the medium transmission speed i With satellites j The propagation delay

[0021] S46) delay the above processing Queuing delay Transmission delay of satellite-to-ground link Propagation delay of satellite-to-ground link Add them together to get the end-to-end transmission delay between the satellite and ground links; add the processing delay Queuing delay Satellites i With satellites j Transmission delay Satellites i With satellites j The propagation delay Add together to get satellite s i With satellites j The two end-to-end transmission delays are used to characterize the satellite transmission performance. The smaller the delay, the better the transmission performance.

[0022] Furthermore, the calculation optimization problem in S5) is performed to obtain an optimal solution, which includes:

[0023] S51) Based on the periodicity of low-orbit satellite motion, the entire satellite network is discretized, and then a model is created to represent the satellite network system based on whether the satellite is under attack. The system state equation is then obtained.

[0024] S52) Construct an optimization problem that satisfies the detection performance:

[0025] S53) Construct an optimization problem that satisfies transmission performance:

[0026] S54) Construct a joint optimization problem that satisfies both detection performance and transmission performance:

[0027] S55) Using the augmented Lagrangian optimization algorithm to solve the above joint optimization problem, the optimal control input for the time period [0, N] is obtained. According to the optimal solution, each satellite is guided to select the best next-hop relay satellite from the set of neighboring nodes along the transmission direction.

[0028] 2. A satellite secure transmission optimization system based on joint anomaly detection, characterized by comprising:

[0029] Anomaly detection mechanism module, used to monitor network status, actively trigger attack detection, and monitor node security in real time;

[0030] The node status assessment module is used to quantitatively assess the impact of network dynamic resources, DoS attacks, and interference attacks on system stability to determine node security, and to evaluate and calculate the satellite's transmission performance based on the node's propagation delay, transmission delay, processing delay, and queuing delay.

[0031] The optimization target module determines the detection target based on minimizing the system detection error and the control target based on the ideal value of the end-to-end transmission delay;

[0032] The optimal control input module constructs a joint optimization problem that satisfies the system detection performance and transmission performance, and uses an optimization algorithm to obtain the optimal control input value;

[0033] The transmission path selection module guides each satellite to select the optimal next-hop relay satellite based on the optimal solution of the joint optimization problem, and repeats the iteration multiple times to obtain a secure end-to-end transmission path.

[0034] Compared with the prior art, the present invention has the following advantages:

[0035] First, the present invention adds anomaly detection in the routing addressing stage and performs routing optimization in combination with detection. In the detection stage, active anomaly detection is adopted, and the anomaly detection mechanism is actively triggered according to the routing addressing results to identify abnormal nodes in a timely manner, thereby improving the robustness of the system.

[0036] Secondly, the present invention takes detection error and detection hysteresis into consideration in the routing stage, takes anomaly detection accuracy as a new constraint for selecting the transmission path and sets the detection target that needs to be met, combines the dynamic network status and the historical behavior of the node, designs the control target according to the quality of service QoS, constructs a joint optimization problem based on the optimization target according to the optimal control theory, and selects the next hop according to the optimal solution of the joint optimization problem, thereby obtaining the optimal transmission path and providing safe and reliable transmission services for business flows in the satellite network.

[0037] Third, the present invention considers the impact of dynamic network resources, DoS attacks, and interference attacks on system stability in its satellite network end-to-end data transmission control optimization algorithm. This allows for real-time monitoring of network status and prompt removal of risky nodes, ensuring the security of end-to-end paths. Furthermore, by combining routing optimization with anomaly detection, adding two-stage bidirectional feedback, and guiding routing selection for secure end-to-end transmission paths based on detection accuracy, the system's robustness is enhanced.

[0038] Simulation results show that the present invention can not only meet the system security and transmission requirements in a network system that is subject to network attacks, but also significantly improve the system robustness. BRIEF DESCRIPTION OF THE DRAWINGS

[0039] Figure 1This is a flowchart of an implementation method for satellite secure transmission optimization based on joint anomaly detection provided by an embodiment of the present invention;

[0040] Figure 2 It is a 3*3 network topology diagram in the method of the present invention;

[0041] Figure 3 This is a module block diagram of a satellite secure transmission optimization system based on joint anomaly detection provided by an embodiment of the present invention.

[0042] Figure 4 Schematic diagram of average data packet transmission delay when using the present invention, the existing SLT transmission mechanism, and the D3QN transmission mechanism for data transmission under different network loads;

[0043] Figure 5 Schematic diagram of the average transmission delay of data packets when data is transmitted using the present invention, the existing SLT transmission mechanism, and the D3QN transmission mechanism under different detection accuracies. DETAILED DESCRIPTION

[0044] In order to make the purpose, technical solutions and advantages of the present invention more clearly understood, the following embodiments of the present invention are further described in detail with reference to the accompanying drawings. It should be understood that the specific embodiments described herein are only used to explain the present invention and are not intended to limit the present invention.

[0045] Example 1: Satellite secure transmission optimization method based on joint anomaly detection

[0046] This example comprehensively considers detection and control performance, proposes a control optimization method based on minimizing control errors to construct a joint optimization problem, and obtains the optimal solution through the augmented Lagrangian optimization algorithm. This guides each satellite to always select the best next-hop satellite, ensuring that data transmission always follows the safest and optimal path.

[0047] Reference Figure 1 The implementation steps of this example include the following:

[0048] Step 1: Construct a time-varying network topology describing the satellite network.

[0049] 1.1) According to the low-orbit satellite constellation configuration, the satellites are numbered according to the number of orbits and the orientation of each orbit to obtain the initial network topology of the constellation:

[0050] Currently, satellites are typically classified into three categories based on their orbital altitude: low-orbit satellites (LEO), medium-orbit satellites (MEO), and high-orbit satellites (GEO).

[0051] Low Earth Orbit (LEO) satellites orbit at altitudes between 500 and 2,000 kilometers. LEO satellites are typically closer to the ground, providing low latency and high communication quality. They are widely used in low-latency communication applications, such as global internet coverage. LEO satellites offer low latency, high data transmission speeds, and excellent signal coverage for users.

[0052] Medium Earth Orbit (MEO) satellites, with an orbital altitude of approximately 2,000-35,000 kilometers, are commonly used for navigation systems and communications. They have a long satellite lifespan and wide signal coverage, making them suitable for wide-area communications. Compared to LEO, MEO orbits are more stable, but data transmission latency is higher.

[0053] High-Earth Orbit (GEO) satellites, also known as geostationary orbit satellites, orbit at an altitude of approximately 35,786 kilometers. GEO satellites rotate synchronously with the Earth and remain above the same location. They are suitable for television broadcasting, meteorological observation, and telecommunications. GEO provides wide coverage without the need for complex ground station adjustments. However, due to its distance from the ground, GEO satellites experience high data transmission latency, and GEO satellites are subject to significant radiation and space weather impacts. Therefore, LEO satellites are currently widely used due to their low latency, high coverage, and low cost. Furthermore, due to the low orbital altitude of LEO, satellite coverage of the Earth is frequent, often requiring the deployment of a large number of satellites to achieve communication missions. This makes low-Earth Orbit (LEO) satellite constellations a popular choice for research.

[0054] Common low-orbit satellite constellations are mainly of the following two types: Iridium and Walker. The Iridium constellation consists of multiple low-orbit satellites, and these satellites are evenly distributed in orbit, forming a specific geometric distribution pattern in orbit. The Iridium constellation has 6 orbital planes, with approximately 11 satellites in each plane, for a total of 66 satellites. By designing the angular distribution and orbital distribution between each satellite, seamless coverage can be ensured worldwide. The Walker constellation is another common low-orbit satellite constellation, also suitable for global communications and data transmission. The Walker constellation uses multiple orbital planes, with the same number of satellites in each plane, and the angles between the planes follow their distribution rules. Through the rational layout of multiple orbital planes and satellites, comprehensive coverage of the Earth's surface is ensured.

[0055] This example uses, but is not limited to, the Iridium constellation configuration. The six orbits are numbered from 1 to 6 according to the 66 satellites in the Iridium constellation. Multiple satellites in the same orbit have the same orbit number.

[0056] The 11 satellites in the same orbit are numbered from 1 to 11. Satellites in the same position but not in the same orbit have the same number.

[0057] The positions of multiple satellites on the same orbit refer to the configuration requirements of the Iridium constellation to construct a network topology map of 6*11 at the initial moment. Satellites are numbered according to the orbit number and position number, and stable links are established between satellites and adjacent satellites.

[0058] Specifically, select a 3*3 part of the network topology, such as Figure 2 As shown, it includes orbit 1, orbit 2 and orbit 3. Three groups of satellites are selected on each orbit, corresponding to azimuth 1, azimuth 2 and azimuth 3 respectively; according to their orbit numbers, the azimuth numbers are numbered as follows: (1,1), (1,2), (1,3), (2,1), (2,2), (2,3), (3,1), (3,2), (3,3).

[0059] 1.2) Use low-orbit satellites to form co-orbit inter-satellite links with the low-orbit satellite nodes before and after them in the same orbit, and use satellites in the same position on adjacent orbits to form inter-orbit inter-satellite links:

[0060] Currently, there is a need for communication between satellites, which requires the construction of inter-satellite links (ISLs) between satellites and adjacent satellites. Adjacent satellites are categorized as co-orbital and non-orbital, depending on whether they are in the same orbit. Two types of ISLs are established for these satellites: co-orbital and non-orbital.

[0061] In a co-orbital inter-satellite link, since the two satellites are in the same orbital plane, the relative positions between the satellites are relatively close, the relative motion between the satellites is consistent, and the signal interference is small. Therefore, the co-orbital inter-satellite link distance is short and the data transmission delay is low;

[0062] In the heterogeneous inter-satellite link, since the two satellites are in different satellite orbits, the relative distance between the satellites is far, and the relative motion between the satellites is large, the inter-satellite link is unstable. In addition, the distance of the heterogeneous inter-satellite link is long, which will lead to a large data propagation delay. However, the heterogeneous inter-satellite link can cover a larger geographical area and provide a more flexible network topology.

[0063] This example comprehensively analyzes both co-orbital and inter-orbital inter-satellite links. Based on link connectivity, it determines the set of neighboring nodes for each satellite. Specifically, it determines the inter-satellite links connected to each satellite based on the satellite constellation configuration and the relative positions between satellites. In this example, each satellite in the satellite network establishes a co-orbital inter-satellite link with two satellites positioned one above and one below it on the same orbit, and an inter-orbital inter-satellite link with two satellites positioned to the left and right of the satellites on different orbits. The relative positions of the satellites remain consistent. While these four inter-satellite links are stable, the performance of each link varies in real time.

[0064] Specifically, the selected 3*3 part of the network topology diagram is as follows: Figure 2 As shown in the figure, (1,1)(1,2)(1,3) are three satellites in the same orbit, and (1,1)(2,1)(3,1) are three satellites in the same position. The intersatellite link between (1,1) and (1,2) is a co-orbital intersatellite link, and the intersatellite link between (1,1) and (2,1) is a cross-orbital intersatellite link. Co-orbital intersatellite links are more stable, while cross-orbital intersatellite links provide more path options for data transmission.

[0065] 1.3) The satellite determines an initial set of neighbor nodes based on the two intersatellite links:

[0066] In a satellite constellation, neighbor satellites are relatively close together, either within the same orbital plane or between different orbital planes. These satellites communicate via intersatellite links (ISLs), enabling intersatellite communication, load balancing, and orbital management coordination to ensure continuous data transmission and efficient system operation. Neighbor satellites are categorized as co-orbital or non-co-orbital, depending on whether they are in the same orbital plane.

[0067] Co-orbital neighbor satellites are satellites in the same orbital plane. They are relatively close to each other and arranged in a specific geometric pattern to ensure coverage of the ground area.

[0068] Neighboring satellites in different orbits are satellites located in different orbital planes, but with the same orbital orientation and a certain proximity. They exchange data via intersatellite links.

[0069] In this example, each satellite determines four inter-satellite links between its four neighboring satellites in front, behind, and on both sides. Based on the connectivity, transmission performance, and security of the four links, the numbers of the neighboring satellites with stable inter-satellite links are stored in a neighbor node set. The neighbor node set is periodically updated based on the real-time system status and satellite motion. This set only stores the numbers of satellites with stable inter-satellite links.

[0070] Specifically, in the selected 3*3 part of the network topology diagram, such as Figure 2 As shown in the figure, for the (2,2) satellite, its four inter-satellite links are: the same-orbit inter-satellite links (2,2)-(2,1) and (2,2)-(2,3); the different-orbit inter-satellite links (2,2)-(1,2) and (2,2)-(3,2). These four inter-satellite links can provide stable inter-satellite transmission, and the numbers of these adjacent satellites are saved in the neighbor node set of the (2,2) satellite. The initial neighbor node set of the (2,2) satellite is: {(2,1), (2,3), (1,2), (3,2)}.

[0071] Step 2: Periodically update the network topology and neighbor node set.

[0072] 2.1) Low-orbit satellites always move periodically along their respective low-orbit orbits. Based on the period of orbital motion, the time-varying network topology is periodically updated to determine the satellite network topology at different times:

[0073] The periodic motion of a satellite refers to the regular changes in its orbit and position over time as it moves along its predetermined orbit. A satellite's orbital motion follows Kepler's laws, completing one complete orbit with each orbit around the Earth. Due to the inclination of the satellite's orbit, the angle of the moving satellite relative to the Earth's surface changes over time. As the satellite orbits, its precise position relative to the ground changes over time.

[0074] The periodic motion of satellites directly impacts the topology of the satellite network, causing the relative positions of satellites to change over time and the inter-satellite links to constantly shift. Due to the rapid movement of satellites, they enter or leave a region over time, causing dynamic changes in the satellite network topology. Furthermore, because the communication links between satellites and their neighbors are time-sensitive, changes in the relative positions and signal strength of satellites can lead to link disconnection. Satellite motion can also cause variations in the signal transmission distance between different satellites, causing latency fluctuations.

[0075] This example is based on the periodic motion of satellites along their orbits. Considering that the satellites' orbital altitude and length are fixed, resulting in periodic motion to the same position in the orbit, the orbital motion period of the satellites in the current satellite constellation configuration is determined to be 90 minutes based on the orbital altitude. At the same time, considering that the satellites' coverage of the ground varies at different locations, the problem of the satellites completely covering the entire low- and mid-latitude regions every 60 minutes is addressed. To better analyze when satellites cover the Earth's low-latitude regions, i.e., service-intensive areas, the present invention sets a 15-minute topology periodic update interval. This means that the satellite positions and intersatellite links are updated every 15 minutes, the network topology is periodically updated, and the satellite network topology at different times is determined.

[0076] 2.2) Based on the periodicity of satellite orbital motion, determine whether a low-orbit satellite has an intersatellite link with satellites in the same or different orbits. Periodically update the neighbor node set of each satellite at the current moment. This set only stores neighbor satellites that maintain a stable intersatellite link with the satellite:

[0077] This example takes into account the periodic changes in satellite position and therefore only selects four adjacent satellites (front, back, left, and right) to establish intersatellite links. These four satellites maintain their relative positions to the satellite, so the same-orbit intersatellite links with the satellites in front and behind them in the same orbit always exist. Intersatellite links with satellites in the same orientation on adjacent orbits also always exist. However, the performance of the four intersatellite links varies constantly, and is closely related to the individual satellite states, the system network state, and system attacks, all of which directly affect link transmission performance. The satellite's neighbor node set is updated based on the link's transmission performance. When an intersatellite link fails to transmit, the satellite number corresponding to that link is removed from the current satellite's neighbor node set.

[0078] Specifically, the present invention evaluates the intersatellite link every 15 minutes to determine whether the intersatellite link can continue to transmit:

[0079] If all four links can achieve inter-satellite transmission, the membership of the neighbor node set does not change;

[0080] If some links cannot achieve inter-satellite transmission, the corresponding satellite number is deleted from the neighbor node set;

[0081] If some links were not available for inter-satellite transmission 15 minutes ago, but are available for inter-satellite transmission at the current time, the corresponding satellite numbers are added from the neighbor node set to implement periodic updates of the satellite neighbor node set.

[0082] Step 3: Detect the satellite network and determine whether the node is safe.

[0083] 3.1) Based on the anomaly detection mechanism, all satellites in the satellite network system are tested to see if they are safe:

[0084] Satellite networks are vulnerable to network threats such as signal interference, communication interruption, eavesdropping and hijacking. Currently, there are many common network attacks. In the satellite network scenario, interference attacks and DoS attacks are typical forms of network attacks.

[0085] DoS attacks paralyze nodes by consuming their resources (such as bandwidth, memory, and computing power), rendering them unable to provide services. Attackers flood target nodes with useless data traffic, exhausting their bandwidth or computing resources. This prevents legitimate requests from being responded to, disrupting system services, depleting network resources, and, in severe cases, causing system crashes. In satellite communications, DoS attacks directly impact satellites, consuming their computing resources and, in severe cases, causing them to crash.

[0086] Jamming attacks disrupt communication signals by sending interfering signals. These signals, including noise or false signals, are transmitted within the target frequency band, preventing the receiver from receiving valid signals. The attacker sends strong RF signals into the communication channel, which overwhelm the valid signals in the target frequency band, disrupting communication and causing system interruption, further degrading system performance. In satellite communications, jamming attacks directly affect the RF link between the satellite and the ground station, resulting in data loss between the satellite and the ground.

[0087] Currently, mainstream anomaly detection mechanisms include statistical, distance, clustering, and machine learning-based methods. Each mechanism distinguishes and identifies abnormal nodes. Statistical anomaly detection is a typical mechanism. It detects anomalies based on the statistical distribution of data. By calculating statistical characteristics such as the mean, standard deviation, and skewness of the data, it determines which data points significantly deviate from the normal distribution and, therefore, whether the data is abnormal.

[0088] This example uses, but is not limited to, a typical statistical-based anomaly detection mechanism to detect all satellites in the satellite network system. The implementation is as follows:

[0089] First, the system continuously monitors potential network attacks, collects and summarizes satellite status data, and detects and judges abnormal data based on the distribution of the collected data. When abnormal data appears, it means that the satellite status is abnormal, which means that the satellite may be under DoS attack or interference attack at the current moment. At this time, the satellite's own transmission performance will decline and further affect the transmission performance of the inter-satellite link related to the satellite. With the help of the anomaly detection mechanism, it is discovered whether there is a network attack and the attacked satellite is located and processed in the first time.

[0090] Secondly, the system's active triggering is detected for anomalies, and based on the detection results, it is determined whether the node has a high security risk, that is, whether the node is vulnerable to network attacks in the future. The node's own state changes are responded to in a timely manner, and reliable satellites are screened to provide a basis for subsequent routing addressing and selection of reliable transit satellites.

[0091] 3.2) Based on the evaluation of the attack level of the quantitative node, determine whether to keep it in the network topology:

[0092] This example uses statistical anomaly detection to determine whether a satellite is under cyber attack. It promptly identifies the attacked satellites and further determines which satellites present a higher risk. Based on the anomaly detection mechanism, unsafe satellites and satellites with low reliability that are attacked are identified and processed accordingly. Attacked satellites are removed from the network topology. For satellites with potential risks, their risk values ​​are quantified and assessed as node processing delays. Further, a determination is made as to whether they should be retained in the network topology. If the node processing delay is controllable, it is temporarily retained in the network topology. If the node processing delay is uncontrollable, it is removed from the network topology. By reducing the likelihood of these satellites being selected during the routing addressing phase, the reliability of routing addressing is ensured, the security of the end-to-end path is enhanced, and the robustness of the system is improved. The specific node processing rules are as follows:

[0093] If the node is not detected to be under network attack, indicating that the node is currently safe, the node is saved in the network topology and the node information is stored in the neighbor node set according to the link relationship, waiting for subsequent routing decisions;

[0094] If it is detected that a node is under network attack, it indicates that the node is currently unsafe. Based on the assessed attack severity of the node, it is determined whether to save it in the network topology.

[0095] If the evaluation result shows that the node is under severe attack, which means that the node is completely unable to continue to carry out subsequent transmission tasks, the node will be directly removed from the neighbor node set and network topology, and the current latest network topology will be updated synchronously;

[0096] If the evaluation node indicates that the node is only under attack but not a severe attack, indicating that the node has not completely lost its transmission capability and can complete subsequent transmission tasks, the node will be temporarily retained in the neighbor node set as a node with controllable attack impact. The impact of the attack on the node transmission is further quantified based on the node's processing delay. The type of attack suffered by the satellite node is determined based on the detection mechanism. Different standards are used to determine the node's transmission performance based on the attack type:

[0097] If a node is detected to be under non-continuous interference attack, it means that the node cannot receive data packets that can be successfully decoded during the attack phase, which will cause node reception interruption and affect node transmission. The impact of the interference attack on the node is characterized by transmission delay calculation;

[0098] If a node is detected to be under a DoS attack of low intensity, it means that the node continuously receives excessive useless data packets during the attack phase, causing node reception interruption and affecting node transmission. The impact of the DoS attack on the node is characterized by the data packet processing delay calculation.

[0099] Step 4: Quantitatively evaluate the node transmission performance.

[0100] In satellite networks, the end-to-end transmission delay of service flows is related to factors such as the transmission path, network load, and node performance, and the variation in delay is mainly caused by the real-time status of the system. This example selects end-to-end delay as a real-time indicator to describe dynamic network changes. The end-to-end delay value of the satellite is quantitatively calculated to represent the real-time status of the satellite. Its implementation includes:

[0101] 4.1) According to satellite s i The load and node function of satellite s i Processing delay and queuing delay

[0102]

[0103] Among them B s is the size of the satellite buffer, S p is the processing rate, Indicates satellite s i The queuing delay of a single data packet, P j Indicates satellite s i The set of data packets that need to be executed, j represents the number of data packets that need to be queued, s d Indicates the destination satellite;

[0104] 4.2) According to satellite s i With ground station g i Position and data packet size, calculate the transmission delay of the satellite-to-ground link

[0105]

[0106] Where D is the amount of data uploaded by the gateway. is the uplink transmission rate, h p represents the channel gain, B represents the bandwidth, σ 2 represents the channel noise power density, and p is the transmit power used by the ground station;

[0107] 4.3) Calculate the propagation delay of the satellite-to-ground link based on the length of the satellite-to-ground link and the transmission speed of the medium

[0108]

[0109] Among them, v d is the propagation speed of the RF link, is the distance of the satellite-to-ground link, and Δt is the propagation time interval of the satellite-to-ground link;

[0110] 4.4) Select the next hop neighbor satellite s j , and calculate satellite s based on the packet sizei With satellites j Transmission delay

[0111]

[0112] in, For satellites i With satellites j The link transmission rate, is the free space loss, Indicates satellite s i With satellites j The satellite line of sight, c and f represent the speed of light and frequency respectively; P t Indicates the signal transmission power, and They represent the transmit antenna gain and receive antenna gain, respectively, k b and T s are the Boltzmann constant and the system noise temperature, respectively. (E b / N o ) r Represents the ratio of energy per bit to noise power density, M a Indicates link margin;

[0113] 4.5) Calculate the satellite s based on the length of the intersatellite link and the medium transmission speed i With satellites j The propagation delay

[0114]

[0115] Where c is the propagation speed of the intersatellite link, is the distance of the intersatellite link, Δt′ is the intersatellite link propagation time interval;

[0116] 4.6) Delay the above processing Queuing delay Transmission delay of satellite-to-ground link Propagation delay of satellite-to-ground link Add together to get satellite s i With ground station g i End-to-end transmission delay of the satellite-to-ground link; processing delay Queuing delay Satellites i With satellites j Transmission delay Satellites i With satellites j The propagation delay Add together to get satellite s i With satellitesj The end-to-end transmission delay of the inter-satellite link is used to characterize the satellite transmission performance using the two obtained end-to-end transmission delays. That is, the smaller the delay, the better the transmission performance.

[0117] 4.7) According to satellite s i The transmission delay, propagation delay, processing delay and queuing delay of satellite s i The total transmission delay is expressed as:

[0118]

[0119] Step 5: Construct a routing control optimization problem that satisfies system robustness and routing optimal performance and obtain the optimal solution.

[0120] With the increasing demand for various communication services from ground users, satellite networks provide new possibilities for all-day and all-time communication services due to their ground coverage. However, with the increase in the scale of satellite networks and the increasing number of satellites, how to schedule and manage satellite communications under limited satellite network resources to provide stable guarantees for a variety of end-to-end services has become an urgent problem to be solved. Control theory is a classic mathematical theory that can solve real-time optimization problems of systems with the help of control inputs. Therefore, this example uses control theory to solve the routing addressing problem of end-to-end services, comprehensively considers the detection requirements and transmission requirements of the system, constructs a joint optimization problem to obtain the optimal solution, and guides the data packet to always be transmitted along the optimal end-to-end path based on the optimal control input, providing a safe and reliable transmission path for various end-to-end services in the satellite network. The calculation process of the optimization problem is as follows:

[0121] 5.1) Based on the periodicity of low-orbit satellite motion, the entire satellite network is discretized and the system state equation is established based on whether the satellite is under attack:

[0122] x k+1|μ =Ax k|μ +Bu k ,

[0123] y k|μ =Cx k|μ ,

[0124] Among them, y k|μ represents the system observation value of the current moment k satellite state μ, x k+1|μ represents the system state where the satellite state is μ at time j+1, Indicates the satellite status, M indicates the number of satellites in the satellite network, u k represents the control input at time k;

[0125] A represents the satellite system characteristic matrix, which is constructed by the current static network topology and the weight values ​​of the four inter-satellite links. Matrix A is updated only when the network topology changes. According to the periodicity of satellite motion, the matrix A is updated at a periodic update interval of 15 minutes, that is, every 15 minutes.

[0126] B represents the satellite system detection matrix, which is used to describe the attack scenario of the satellite network and characterize the security and reliability of each satellite under the presence of a detection mechanism. The matrix is ​​constructed from the quantized values ​​of the satellite state, which includes the satellite's own load and queue length, and clearly distinguishes reliable nodes from unreliable nodes. Specifically, nodes with lower load and smaller queues have higher reliability.

[0127] C represents the unit matrix, which is used to characterize the system observation of each end-to-end service and intuitively represents the change in the end-to-end delay of the service.

[0128] 5.2) Construct an optimization problem that satisfies the detection performance:

[0129] N parallel detection units are deployed in the satellite network to detect various network attacks. The state of each node μ i ,i=1,…,2 p According to the node s i Its own health status, execution status and functional attributes are determined according to the probability P(μ i ) appears; introduce control input adjustment optimization routing addressing results in the satellite network system, based on the control input u k ,k=0,…,N, rewrite the conditional probability of each node state as P(μ i |u 0:N In order to improve the effectiveness of the anomaly detection mechanism, especially the judgment of potential risk satellites, a multi-model adaptive estimator is used to calculate the posterior probability based on the rewritten node state conditional probability P(μ i |u 0:N ) to further determine the system status.

[0130] 5.2.1) Define detection accuracy as the system's ability to accurately locate the attacked satellite and set the system state μ i The conditional probability P(μ i |y 0:N ,u 0:N-1 ), which is given by P(μ i |u 0:N-1 ) and P(y 0:N |u 0:N-1 ) is approximately multiplied to obtain, where P(μ i |u 0:N-1 ) represents the control input u at time N-1 0:N-1 Satellite state μi The probability value of occurrence, P(μ i |y 0:N ) represents the system observation value y at time N 0:N Satellite state μ i The probability value of occurrence, 0:N represents the time period [0,N];

[0131] 5.2.2) Probability P(μ) based on system state i |y 0:N ,u 0:N-1 ) Calculate the detection target J d :

[0132]

[0133] in, The value is 0 or 1, when there is no attack on the satellite network system The value is 0, in other states The value is 1;

[0134] 5.2.3) To simplify the calculation, determine the detection target J d The upper bound of for:

[0135]

[0136] Among them, P(μ i ) and P(μ j ) represent two different node states μ i and μ j The probability of occurrence, φ ij Represents the two node states μ i With μ j The difference between the two is expressed as follows:

[0137]

[0138] Where, is the i-th state μ of the node i The covariance matrix based on the system observation y is as follows: is the j-th state μ of the node j The covariance matrix based on the system observation y is as follows: and Represent two different states μ i and μ j The corresponding average system observation value;

[0139] 5.3) Construct an optimization problem that satisfies transmission performance:

[0140] 5.3.1) Define rk represents the ideal value at the current time k, where the satellite is in good condition without attack, the link is fault-free, the network traffic is not congested, and the transmission decision is successfully made. It is expressed as:

[0141] r k =T trans +T prop +T proc +T queue ,

[0142] Among them, T trans 、T prop 、T proc and T queue They are the transmission delay value, propagation delay value, processing delay value and queuing delay value corresponding to the ideal situation respectively;

[0143] 5.3.2) According to the ideal value r k and input value u k The cost value determines the control target J c :

[0144]

[0145] in, is a positive semidefinite matrix, is a positive definite matrix, Indicates the input value u k The corresponding cost value, Indicates the control error value;

[0146] 5.3.3) To simplify the calculation, the control objective is rewritten as:

[0147]

[0148] Among them, 2 p represents the total number of states of the system,

[0149]

[0150] Where, Indicates that the system state at the initial moment is in the i-th state μ i The average value of Represents the i-th state μ i The detection matrix value of represents the mean value of the system state, Represents the system observation value y and the i-th state μ i The covariance matrix of .

[0151] 5.4) According to the set detection target J d and control target J c, the joint optimization problem is constructed:

[0152]

[0153] in, Indicates the optimal control input value in the current time period, n represents the number of constraints in the system, Characterize the multiple constraints that need to be met in the system;

[0154] 5.5) The augmented Lagrangian optimization algorithm is used to iteratively solve the above joint optimization problem and obtain the optimal control input for the time period [0, N]

[0155] 5.6) According to the input, each satellite is guided to select the best next-hop relay satellite from the set of neighboring nodes along the transmission direction:

[0156] 5.6.1) The satellite determines the members of its own neighbor node set, and traverses the control input values ​​corresponding to each member in turn, and calculates the control input values ​​according to the optimal control input. Sort the members by their difference values ​​from small to large;

[0157] 5.6.2) The satellite determines the location of the destination satellite, compares the positions of each member, and sorts the members according to the direction of the destination node;

[0158] 5.6.3) Based on the results of steps 5.6.1) and 5.6.2), select the satellite with the smallest difference value and the direction that meets the destination node from the neighbor node set as the optimal next hop node.

[0159] This example iteratively calculates the optimization problem for each relay satellite. In each round, the best next-hop relay satellite is selected and stored in a transmission path set in the transmission order until the next-hop relay satellite is the destination satellite. At this time, the end-to-end optimal transmission path corresponding to the data packet is obtained based on the transmission path set, guiding the low-orbit satellites to achieve end-to-end secure transmission along the transmission path.

[0160] The flowchart representations or method representations of the above embodiments can be understood as representing a module, segment, or portion of code comprising one or a group of executable instructions configured to implement a specific logical function or process. The present invention is not limited to the disclosed preferred embodiments, and its implementation may not follow the order presented or discussed. That is, the step numbers in the present specification and claims are merely for the purpose of clarifying the embodiments of the present invention and facilitating understanding, and the order of the numbering is not limiting.

[0161] Example 2: Satellite secure transmission optimization system based on joint anomaly detection

[0162] Reference Figure 3 This example includes: an anomaly detection mechanism module 1, a node state assessment module 2, an optimization target module 3, an optimal control input module 4, and a transmission path selection module 5. The node state assessment module 2 includes a node security submodule 21 and a node stability submodule 22, and the optimal control input module 4 includes a joint optimization problem construction submodule 41 and an optimization problem solving submodule 42. The working principle of the entire system is as follows:

[0163] The anomaly detection mechanism module 1 is used to monitor the network status, actively trigger attack detection, monitor node security in real time, and transmit the detection results to the node status assessment module 2;

[0164] The node status evaluation module 2 is used to quantitatively evaluate the impact of the network's dynamic resources, DoS attacks and interference attacks on system stability to determine node security, wherein the node security submodule 21 makes a judgment based on the detection result of the anomaly detection mechanism module 1, and transmits the judgment result to the optimization target module 3 and the optimal control input module 4; the node stability submodule 22 calculates the node's propagation delay, transmission delay, processing delay and queuing delay to evaluate the satellite's transmission performance, and transmits the evaluation result to the optimization target module 3 and the optimal control input module 4;

[0165] The optimization target module 3 determines the detection target based on minimizing the system detection error and the control target based on the ideal value of the end-to-end transmission delay according to the evaluation results transmitted by the node safety submodule 21 and the node stability submodule 22, and transmits the constructed detection target and control target to the optimal control input module 4;

[0166] The optimal control input module 4 constructs a joint optimization problem that satisfies both detection performance and transmission performance, wherein the joint optimization problem construction submodule 41 constructs a joint optimization problem based on the results transmitted by the node state evaluation module 2 and the optimization target module 3, and transmits the optimization problem to the optimization problem solving submodule 42. The optimization problem solving submodule 42 uses an optimization algorithm to obtain an optimal control input value based on the results transmitted by the joint optimization problem construction submodule 41, and transmits the calculated optimal solution to the transmission path selection module 5;

[0167] The transmission path selection module 5 guides each satellite to select the optimal next-hop relay satellite based on the optimal solution of the joint optimization problem according to the results transmitted by the optimization problem solving submodule 42, and repeats the iteration multiple times to obtain a secure end-to-end transmission path.

[0168] It should be noted that the above-mentioned functional modules can be implemented in whole or in part through software, hardware, firmware, or any combination thereof. When implemented using software, they can be implemented in whole or in part in the form of a program instruction product. The program instruction product includes one or a group of program instructions. When the program instructions are loaded and executed on a computer, the process or function described is generated in whole or in part. The computer can be a general-purpose computer, a special-purpose computer, a computer network, or other programmable device. The program instructions can be stored in a computer-readable and writable storage medium, or transferred from a computer-readable and writable storage medium to another computer-readable and writable storage medium.

[0169] The direct coupling or communication connection between the modules shown or discussed in this embodiment can be achieved through indirect coupling or communication connection of some interfaces, devices or modules. The various functional modules and submodules in this embodiment can be dynamically located in a processing component, or each module can exist physically separately, or two or more modules can be dynamically located in a processing component. When the above-mentioned dynamic components are implemented in the form of software functional modules and sold or used as independent products, they can also be stored in a computer-readable and writable storage medium. The storage medium can be a memory, a magnetic disk, an optical disk, etc.

[0170] The effects of the present invention can be further illustrated by the following simulation.

[0171] 1. Simulation conditions:

[0172] The simulation sets up an Iridium constellation with six orbits, each with 11 satellites (including backup satellites). The ground network consists of a gateway, a ground control center, and a large number of terminals.

[0173] Fourteen gateway stations and one ground control center are set up according to longitude and latitude. The specific locations of the gateway stations are shown in Table 1.

[0174] Set N = 7 detection units. Generate a traffic demand matrix based on the population and economic output of popular cities, and obtain the traffic demand matrix of 14 ground stations according to the traffic model.

[0175] The satellite network parameters are set according to the satellite orbit GP information obtained from the TLE website as shown in Table 2.

[0176] The Python platform is used to implement the complete transmission process, analyze the traffic flow between 14 ground stations, and simulate multiple pairs of traffic flows with different path lengths. The specific simulation parameters are shown in Table 3.

[0177] Jamming attack and DoS attack are set in the satellite network, and the attack parameters are shown in Table 4.

[0178] Table 1 Gateway

[0179]

[0180] Table 2 Low-orbit satellite network parameters

[0181]

[0182] Table 3 Simulation parameter settings

[0183]

[0184] Table 4 Attack parameter settings

[0185]

[0186] 2. Simulation content:

[0187] Simulation 1: Under the above conditions, the present invention, the existing SLT algorithm, and the D3QN algorithm are used to simulate the construction of secure end-to-end transmission paths that meet the service requirements of 14 continuous service flows based on different source nodes and destination nodes in the Iridium satellite network. The three transmission schemes are simulated to simulate the system end-to-end service performance under interference attacks and DoS attacks under different network loads. The end-to-end delay under different network loads is calculated, that is, the sum of propagation delay, sending delay, and queuing delay. The results are as follows: Figure 4 ,in:

[0188] Figure 4 (a) is the end-to-end delay of the service flow under different network loads with interference attacks,

[0189] Figure 4 (b) is the end-to-end delay of the service flow under different network loads with DoS attacks.

[0190] Depend on Figure 4 (a) It can be seen that the SLT algorithm can only select the optimal next-hop node based on node behavior. Although the D3QN algorithm considers the node trust value and jointly selects the next-hop node based on the link status, it cannot respond to attacks in a timely manner. The present invention considers not only the node transmission performance but also the node security performance in link selection, and can promptly and proactively trigger anomaly detection and identify threat nodes.

[0191] When the network load is light, the SLT and D3QN algorithms determine the end-to-end transmission path for the service flow based on the additional bandwidth resources in the network system. At this time, the end-to-end delay increases significantly with the increase of network load. The secure transmission scheme proposed in this invention judges interference attacks based on active detection, actively evaluates the impact of attacks on nodes based on the current state, and selects the optimal end-to-end path by combining node security indicators and performance indicators. By pre-judging the node status in advance, the optimal end-to-end transmission path can be determined for the service flow. It can also provide good transmission performance as the network load increases, and the end-to-end delay changes slightly.

[0192] In summary, when the network load is light, interference attacks may hinder the normal reception of data packets, but sufficient bandwidth resources provide redundant bandwidth for data transmission. All three transmission methods can establish a good end-to-end transmission path. However, when the load is heavy, bandwidth resources are scarce. Because the joint detection and secure transmission scheme proposed in this invention accounts for errors in detection accuracy and effectively selects nodes that are not affected by interference attacks, it can consistently ensure the stability of end-to-end transmission.

[0193] Depend on Figure 4 (b) It can be seen that DoS attacks cause link interruptions by blocking nodes. After successfully detecting the attack, it is decided whether to remove the victim node. The SLT algorithm measures the security of nodes by trust value and promptly removes nodes attacked by DoS; the D3QN algorithm considers the node trust value and link status to remove attacking nodes. When the network load is light, the three secure transmission algorithms can successfully avoid DoS attacks and select a secure path for end-to-end services. However, when the network load is heavy, the node's own load status increases. At this time, the proportion of high-load and attacked nodes in the network increases. The SLT algorithm and the D3QN algorithm can only select high-load nodes as transit nodes. At this time, the end-to-end transmission delay increases significantly. The present invention can not only quickly identify attacks, but also evaluate the node status and quantify the attacked nodes, which can avoid selecting transit nodes with excessive loads. As the network load increases, the end-to-end delay changes can be controlled, always ensuring the security and stability of end-to-end transmission.

[0194] Simulation 2: Under the above conditions, the present invention and the existing SLT algorithm and D3QN algorithm are used to simulate the construction of secure end-to-end transmission paths that meet the service needs of 14 continuous service flows based on different source nodes and destination nodes in the Iridium satellite network. A detection mechanism is deployed in the Iridium satellite network system with detection accuracies of 50 times / min, 100 times / min, 150 times / min, 200 times / min, 250 times / min, and 300 times / min, respectively. The system end-to-end service performance of the three transmission schemes under different detection accuracies against interference attacks and DoS attacks is simulated, and the end-to-end delay of different network loads is calculated, that is, the sum of propagation delay, sending delay, and queuing delay. The results are as follows: Figure 5 As shown, where:

[0195] Figure 5 (a) is the end-to-end delay of the service flow with different detection accuracy in the presence of interference attacks,

[0196] Figure 5 (b) End-to-end delay of service flows with different detection accuracies in the presence of DoS attacks.

[0197] Depend on Figure 5 (a) As can be seen, the SLT and D3QN algorithms can only periodically check whether the system is under interference attacks based on a fixed detection frequency. Although this improves system transmission performance as detection accuracy increases, they cannot promptly identify interference attacks, and therefore use nodes under interference attacks as transit nodes in the end-to-end transmission path. The secure transmission scheme proposed in this invention, on the other hand, simultaneously factors in a node's historical behavior and detection accuracy as decision-making factors, proactively triggers a detection mechanism for interference attacks, and prioritizes secure and reliable nodes in the end-to-end transmission path, ensuring that end-to-end transmission latency is always optimized.

[0198] from Figure 5 (a) It can also be seen that when the detection accuracy is low, the end-to-end transmission delay of the SLT algorithm and the D3QN algorithm is large. The present invention can quickly locate the node attacked by interference, maintain good detection performance when the detection accuracy is reduced, and can always deploy the optimal end-to-end transmission path for the service flow.

[0199] Depend on Figure 5(b) It can be seen that the SLT and D3QN algorithms can only periodically check whether the system is under DoS attack based on a fixed detection frequency. Detected DoS attack nodes are directly removed from the network topology without being able to promptly restore these nodes, significantly increasing the number of hops and end-to-end latency of the end-to-end transmission path. The secure transmission solution proposed in this invention quantitatively evaluates the performance of nodes attacked by DoS, promptly detects and quickly adds restored nodes to the network topology, and retains low-risk nodes. This reduces the impact of detection accuracy on transmission path security and consistently selects the optimal end-to-end transmission path.

[0200] from Figure 5 (b) It can also be seen that when the detection accuracy is low, the SLT algorithm and the D3QN algorithm can only select paths with longer hops for data transmission, and the end-to-end delay is large. However, the present invention always determines a transmission path with shorter hops for the business flow and always ensures the security of the end-to-end transmission path.

Claims

1. A satellite security transmission optimization method based on joint anomaly detection, characterized in that: include: S1) Based on the constellation configuration, the connection relationship between the satellite and its adjacent satellites is clarified, the set of neighbor nodes of the satellite is determined, and a time-varying network topology describing the satellite network is constructed; S2) periodically updating the network topology and the satellite's neighbor node set according to the satellite's periodic motion along the orbit; S3) Based on the anomaly detection mechanism, the network status is monitored in real time to promptly determine whether the current network is subject to interference attacks and DoS attacks, periodically update the node status including transmission status and security status, and determine whether the current satellite can transmit data safely; S4) Quantitatively evaluate node transmission performance, determine node transmission performance based on end-to-end latency, and select low-latency, high-performance nodes for secure and reliable transmission; S5) determining a routing control optimization problem that satisfies system robustness and routing optimal performance based on the current network topology and the constructed neighbor node set, based on link selection indicators such as node status, link hop count, detection accuracy, node load, and link transmission delay, and based on the needs of the source and destination satellites; The optimal solution to the optimization problem is obtained by calculation. Based on the optimal solution, each satellite is guided to select the best relay satellite that can transmit safely from the set of neighboring nodes along the transmission direction, and the end-to-end optimal transmission path is obtained in the current network topology.

2. The method according to claim 1, wherein Said S1) constructs a time-varying network topology describing the satellite network, and its implementation includes the following; S11) numbering the satellites according to the low-orbit satellite constellation configuration and the number and orientation of each low-orbit satellite in the orbit, to obtain an initial network topology of the constellation; S12) using the low-orbit satellite to form a co-orbit inter-satellite link with the low-orbit satellite nodes before and after it in the same orbit, and to form a different-orbit inter-satellite link with the satellite in the same position on the adjacent orbit; S13) The satellite determines an initial set of neighbor nodes according to the two inter-satellite links.

3. The method according to claim 1, wherein In said S2), according to the law of the satellite's periodic motion along the orbit, the network topology and the satellite's neighbor node set are periodically updated, and its implementation includes the following: S21) The low-orbit satellites always move periodically along their respective low-orbit orbits. According to the period of the orbital motion, the time-varying network topology is periodically updated to determine the satellite network topology at different times. S22) Based on the periodicity of satellite orbital motion, periodically determine whether intersatellite links exist between low-orbit satellites and satellites in the same satellite orbit and different satellite orbits, and periodically update the neighbor node set of each satellite at the current moment. This set only stores neighbor satellites that maintain stable intersatellite links with the satellite.

4. The method according to claim 1, wherein In S3), it is determined whether the current node can transmit data securely, and its implementation includes the following: S31) All satellites in the satellite network system are tested to determine if they are safe according to the anomaly detection mechanism: If the node is not detected to be under network attack, indicating that the node is currently safe, the node is saved in the network topology and the node information is stored in the neighbor node set according to the link relationship, waiting for subsequent routing decisions; If it is detected that the node is under network attack, indicating that the node is currently unsafe, then S32 is executed; S32) determining whether to store the node in the network topology based on the evaluation and quantification of the attack level suffered by the node; If the evaluation result shows that the node is under severe attack, which means that the node is completely unable to continue to carry out subsequent transmission tasks, the node will be directly removed from the neighbor node set and network topology, and the current latest network topology will be updated synchronously; If the evaluation node indicates that the node is only under attack but not a severe attack, indicating that the node has not completely lost its transmission capability and can complete subsequent transmission tasks, the node will be temporarily retained in the neighbor node set as a node with controllable attack impact. The impact of the attack on the node transmission is further quantified based on the node's processing delay. The type of attack suffered by the satellite node is determined based on the detection mechanism. Different standards are used to determine the node's transmission performance based on the attack type: If a node is detected to be under non-continuous interference attack, it means that the node cannot receive data packets that can be successfully decoded during the attack phase, which will cause node reception interruption and affect node transmission. The impact of the interference attack on the node is characterized by transmission delay calculation; If a node is detected to be under a DoS attack of low intensity, it means that the node continuously receives excessive useless data packets during the attack phase, causing node reception interruption and affecting node transmission. The impact of the DoS attack on the node is characterized by the data packet processing delay calculation.

5. The method according to claim 1, wherein S4) Quantitatively evaluate node transmission performance, determine node transmission performance based on end-to-end latency, and select low-latency, high-performance nodes for secure and reliable transmission; S41) According to satellite s i The load and node function of satellite s i Processing delay and queuing delay Among them B s is the size of the satellite buffer, S p is the processing rate, Indicates satellite s i The queuing delay of a single data packet, P j Indicates satellite s i The set of data packets that need to be executed, j represents the number of data packets that need to be queued, s d Indicates the destination satellite; S42) According to satellite s i With ground station g i Position and data packet size, calculate the transmission delay of the satellite-to-ground link Where D is the amount of data uploaded by the gateway. is the uplink transmission rate, h p represents the channel gain, B represents the bandwidth, σ 2 represents the channel noise power density, and p is the transmit power used by the ground station; S43) Calculate the propagation delay of the satellite-to-ground link based on the length of the satellite-to-ground link and the medium transmission speed Among them, v d is the propagation speed of the RF link, is the distance of the satellite-to-ground link, and Δt is the propagation time interval of the satellite-to-ground link; S44) Select the next hop neighbor satellite s j , and calculate satellite s based on the packet size i With satellites j Transmission delay in, For satellites i With satellites j The link transmission rate, is the free space loss, Indicates satellite s i With satellites j The satellite line of sight, c and f represent the speed of light and frequency respectively; P t Indicates the signal transmission power, and They represent the transmit antenna gain and receive antenna gain, respectively, k b and T s are the Boltzmann constant and the system noise temperature, respectively. (E b / N o ) r Represents the ratio of energy per bit to noise power density, M a Indicates link margin; S45) Calculate the satellite s according to the length of the intersatellite link and the medium transmission speed i With satellites j The propagation delay Where c is the propagation speed of the intersatellite link, is the distance of the intersatellite link, Δt′ is the intersatellite link propagation time interval; S46) delay the above processing Queuing delay Transmission delay of satellite-to-ground link Propagation delay of satellite-to-ground link Add them together to get the end-to-end transmission delay between the satellite and ground links; add the processing delay Queuing delay Satellites i With satellites j Transmission delay Satellites i With satellites j The propagation delay Add together to get satellite s i With satellites j The two end-to-end transmission delays are used to characterize the satellite transmission performance. The smaller the delay, the better the transmission performance. The total transmission delay is calculated as:

6. The method according to claim 1, wherein In S5), a routing control optimization problem that satisfies system robustness and routing optimal performance is determined and an optimal solution is obtained by calculating the optimization problem. The implementation of the problem includes the following steps: S51) Based on the periodicity of low-orbit satellite motion, the entire satellite network is discretized, and then a model is created to represent the satellite network system based on whether the satellite is under attack. The system state equation is: x k+1|μ =Ax k|μ +Bu k , y k|μ =Cx k|μ , Among them, y k|μ represents the system observation value of the current moment k satellite state μ, x k+1|μ represents the system state where the satellite state is μ at time k+1, Indicates the satellite status, M indicates the number of satellites in the satellite network, u k represents the control input at time k; A represents the satellite system characteristic matrix, which is constructed by the network topology and the weights of each link. The matrix A is updated only when the network topology changes, that is, it is updated every 15 minutes. B represents the satellite system detection matrix, which is used to describe the attack situation of the satellite network. It is constructed by the quantized calculated value of the satellite state, which includes the satellite's own load and queue length; C represents the identity matrix, which is used to represent the system observation of each end-to-end service; S52) Construct an optimization problem that satisfies the detection performance: Detection accuracy is defined as the system's ability to accurately locate the attacked satellite, and the probability of detection error is set to determine the detection target: Among them, P(μ i |y 0:N ,uy 0:N-1 ) represents the state μ i The conditional probability value of P(μ i |u 0:N-1 ) and P(y 0:N |u 0:N-1 ) is calculated, The value is 0 or 1, when there is no attack on the satellite network system The value is 0, in other states The value is 1; P(μ i |u 0:N-1 ) represents the control input u at time N-1 0:N-1 Satellite state value μ i The probability value of occurrence; P(μ i |y 0:N ) represents the system observation value y at time N 0:N Satellite state μ i The probability value of occurrence, 0:N represents the time period [0,N]; S53) Construct an optimization problem that satisfies transmission performance: Define r k It represents the ideal value at the current time k, when the satellite is in good condition without attack, the link is fault-free, the network traffic is not congested, and the transmission decision is successfully made. Its formula is expressed as: r k =T trans +T prop +T proc +T queue , Among them, T trans 、T prop 、T proc and T queue They are the transmission delay value, propagation delay value, processing delay value and queuing delay value corresponding to the ideal situation respectively; According to the ideal value r k and input value u k The cost value determines the control target as: in, is a positive semidefinite matrix, is a positive definite matrix, Indicates the input value u k The corresponding cost value; S54) Construct a joint optimization problem that satisfies both detection performance and transmission performance: According to the set detection target J d and control target J c , the joint optimization problem is constructed: in, Indicates the optimal control input value in the current time period, n represents the number of constraints in the system, Characterize the multiple constraints that need to be met in the system; S55) Using the augmented Lagrangian optimization algorithm to solve the above joint optimization problem, the optimal control input for the time period [0, N] is obtained. According to the optimal solution, each satellite is guided to select the best next-hop relay satellite from the set of neighboring nodes along the transmission direction.

7. The method according to claim 1, wherein In S5), the end-to-end optimal transmission path is obtained in the current network topology, which is an iterative solution to the joint optimization problem. The best next-hop relay satellite is selected in each round; these relay satellites are then saved in the transmission path set in sequence according to the transmission order until the next-hop relay satellite is the destination satellite. At this time, the end-to-end optimal transmission path corresponding to the data packet is obtained according to the transmission path set.

8. A satellite security transmission optimization system based on joint anomaly detection, characterized in that: include: Anomaly detection mechanism module, used to monitor network status, actively trigger attack detection, and monitor node security in real time; The node status assessment module is used to quantitatively assess the impact of network dynamic resources, DoS attacks, and interference attacks on system stability to determine node security, and to evaluate and calculate the satellite's transmission performance based on the node's propagation delay, transmission delay, processing delay, and queuing delay. The optimization target module determines the detection target based on minimizing the system detection error and the control target based on the ideal value of the end-to-end transmission delay; The optimal control input module constructs a joint optimization problem that satisfies the system detection performance and transmission performance, and uses an optimization algorithm to obtain the optimal control input value; The transmission path selection module guides each satellite to select the optimal next-hop relay satellite based on the optimal solution of the joint optimization problem, and repeats the iteration multiple times to obtain a secure end-to-end transmission path.

9. The system according to claim 8, characterized in that The node status assessment module includes: The node security submodule is used to determine whether the current node is safe. It determines whether the satellite is under DoS attack or interference attack based on the anomaly detection mechanism, removes satellites that pose a serious threat from the network topology, and updates the system topology. For satellites that pose no serious threat, it quantifies the impact of the current node status on the system through queuing delay and downtime. The node stability submodule is used to quantitatively evaluate the transmission performance of the current node and calculate the satellite's transmission performance based on the node's propagation delay, transmission delay, processing delay, and queuing delay.

10. The system according to claim 8, wherein: The optimal control input module includes: The joint optimization problem construction submodule is used to construct an optimization problem that satisfies the current data packet transmission performance and detection performance. The joint optimization problem is obtained based on the control objectives, system constraints, and the upper limit of the detection target to be met. The optimization problem solving submodule is used to solve the optimal control input value and iteratively guide the satellite to select the best next-hop relay satellite from the set of neighboring nodes based on the optimal solution.

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