Anti-interference secure transmission method of wireless sensor network

Abstract

The invention relates to the field of communication transmission, and discloses an anti-interference secure transmission method for a wireless sensor network, which comprises the following steps of: acquiring residual electric quantity, position and communication quality parameters of a sensor node in real time; dynamically selecting a multi-hop routing path based on interference detection, excluding low-electric-quantity nodes, and preferentially selecting high-electric-quantity and low-interference area nodes to form a main path; at least one independent redundant path is generated according to the node electric quantity distribution and the interference intensity, and the relay node electric quantity of the redundant path is higher than a threshold value; monitoring electric quantity change in real time, and triggering a route dynamic reconstruction mechanism; and recovering complete information through a data fusion and verification algorithm. In addition, a charging request protocol is triggered for a low-power key node. According to the invention, by optimizing routing selection, redundancy transmission and energy management strategies, the anti-interference capability and transmission reliability of the wireless sensor network are improved, and the problem of data interruption caused by insufficient electric quantity of nodes is avoided.

Description

Technical Field

[0001] The present invention relates to the field of communication transmission, and in particular to an anti-interference safety transmission method for a wireless sensor network. Background Art

[0002] Wireless sensor networks (WSNs) are networks composed of a large number of low-power, low-cost sensor nodes used to monitor and collect environmental data. Due to their widespread use in military, medical, and environmental monitoring applications, the security and reliability of WSNs are crucial. However, WSNs face numerous security threats, particularly jamming attacks, which can lead to data loss, network outages, and even complete network failure.

[0003] A jamming attack occurs when an attacker sends jamming signals to disrupt wireless communications in a wireless sensor network (WSN), thereby affecting the integrity and reliability of data transmission. Jamming attacks can be categorized into two types: active jamming and passive jamming. Active jamming occurs when an attacker intentionally sends jamming signals to disrupt normal communications in a wireless sensor network (WSN). Passive jamming involves natural interference sources in the environment, such as electromagnetic interference (EMI) and signal interference from other wireless devices.

[0004] To combat jamming attacks and improve the anti-jamming capabilities of wireless sensor networks (WSNs), various anti-jamming secure transmission methods have been proposed. One of these methods is multi-hop routing and redundant transmission. This method uses multi-hop routing technology to transmit data to its destination via multiple relay nodes, increasing redundancy and reliability.

[0005] However, when multi-hop routing and redundant transmission are used to deal with interference attacks on wireless sensor networks (WSNs), when there are a large number of low-battery sensor nodes in the network, that is, with battery power below 20%, data transmission will be interrupted or lost due to insufficient node power. Summary of the Invention

[0006] The purpose of the present invention is to provide an anti-interference secure transmission method for wireless sensor networks, which solves the technical problem of optimizing multi-hop routing and redundant transmission strategies while ensuring data transmission reliability, and avoiding data transmission interruption or loss due to insufficient node power.

[0007] The purpose of the present invention can be achieved through the following technical solutions: A method for secure transmission of wireless sensor networks with anti-interference comprises the following steps: Step S1: Acquire the remaining power, location information and communication quality parameters of each sensor node in real time; Step S2: When sending data from the source sensor node, a multi-hop routing path is dynamically selected based on the real-time interference detection results, where: When selecting a path, sensor nodes with a remaining battery power lower than a preset threshold are excluded as relay nodes; The sensor nodes that are ranked in the top X in descending order of remaining power and are located in a low-interference area are preferentially selected to form the main transmission path; the low-interference area is obtained by the following method: The node periodically samples the channel idle rate CCA, bit error rate BER, and signal strength fluctuation value F, and calculates the variance or root mean square error RMSE of the RSSI sequence as F; ; like ≥ , it is determined to be a high interference area; if < , determined as a low interference area; If the BER rises by 50% within three consecutive cycles and the signal strength variance exceeds the threshold, it is determined to be under active jamming attack; Step S3: During redundant transmission, at least two independent redundant paths are generated based on the remaining power distribution of the sensor nodes and the interference intensity, and the remaining power of all relay nodes in the redundant paths is higher than a preset threshold; Step S4: During data transmission, the remaining power of the relay nodes is monitored in real time. If the remaining power of at least one sensor node drops below a preset threshold, the dynamic routing reconstruction mechanism is triggered to reselect the path and migrate the data to the new path. Step S5: After the convergent sensor node receives the primary path and redundant path data, it restores the complete information through data fusion and verification algorithms.

[0008] As a further technical solution, the dynamic selection of a multi-hop routing path in step S2 further includes: A comprehensive scoring model is used to score each path. The scoring factors include the remaining battery power of the sensor node, the historical packet loss rate, the current interference intensity and the number of hops. Arrange each path in descending order according to the score, where the path ranked first is the main path and the path ranked second is the redundant candidate path.

[0009] As a further technical solution, the expression of the comprehensive scoring model is: ; ; in, 、 、 、 is the adjustment coefficient, =1.5, =3, =2, =10, For the The rating of sensor nodes, For the The remaining power of each sensor node, For the The current interference strength of each sensor node, is the interference intensity threshold, is the baseline reliability coefficient, No. The historical reliability coefficient of each sensor node is calculated as follows: ; is the number of path hops, is the maximum allowed number of hops, is the delay coefficient, is the end-to-end delay coefficient, , is the processing delay of the current sensor node, is the waiting time of the data packet in the current sensor node buffer queue, is the wireless transmission delay of the current sensor node.

[0010] As a further technical solution, the redundant path generation in step S3 adopts the following strategy: Using the disjoint path algorithm in graph theory, we search for m paths as redundant paths in the network topology, excluding sensor nodes whose remaining battery power is lower than a preset threshold, where m ≥ 2. The redundant paths satisfy the following conditions: the sum of the interference strength is less than the interference strength threshold, and they are in the first m positions after being sorted in ascending order. Redundant data packets use fragmentation encoding technology to ensure that the original data can be restored if any two paths are successfully transmitted.

[0011] As a further technical solution, the method further includes: Step S6: For key nodes whose remaining power is continuously lower than a preset threshold and cannot be bypassed by routing, a charging request protocol is triggered, and directed energy replenishment is performed through drones or mobile charging devices.

[0012] As a further technical solution, the generation of the independent redundant path satisfies the following conditions: The redundant path and the main transmission path do not intersect in physical space, and the relay node set does not overlap with the main path; The sum of the interference strengths of redundant paths Both are less than the interference intensity threshold , where the calculation formula for the total interference intensity is: , The redundant path The current interference strength of relay nodes, is the number of redundant path hops.

[0013] As a further technical solution, when it is detected that the remaining power of the relay node is lower than a preset threshold, the local route discovery protocol is triggered to search for an alternative node in the neighborhood of the current path with a remaining power higher than the threshold and an interference strength lower than the interference strength threshold; If there is no available alternative node in the neighborhood, global routing reconstruction is initiated, and the primary path and redundant path are recalculated based on the current network topology to ensure that the comprehensive score of the new path does not decrease by more than X% of the original path, where X% is 30%.

[0014] As a further technical solution, the data fusion and verification algorithm in step S5 adopts the following strategy: Perform XOR check on data packets on the primary and redundant paths, and use the checksum to identify data packet damage caused by transmission errors or interference; When the primary path data is lost or erroneous, the redundant path data is used to restore the original information through the maximum likelihood estimation algorithm. The recovery success rate must meet the following requirements: Where, The number of valid data packets on the main path, is the number of valid data packets on the redundant path, is the recovery efficiency coefficient.

[0015] Beneficial effects of the present invention: (1) By collecting multi-dimensional parameters of node power and interference intensity in real time, the main path and redundant path are dynamically selected in combination with a comprehensive scoring model; the main path prioritizes nodes in high-power and low-interference areas to avoid transmission interruptions caused by insufficient node power or strong interference; the redundant path is generated through a graph-theoretic non-intersection algorithm, physically isolated from the main path and with controllable interference, ensuring that data can still be transmitted through an independent path when the main path fails; at the same time, the real-time monitoring of power triggers the routing reconstruction mechanism, which combines local neighborhood search with global path calculation to quickly respond to node status changes, effectively reduce interference impacts and data loss risks, and form a complete anti-interference link system covering path selection, redundant backup, and dynamic repair; (2) By excluding low-power nodes from participating in relays and giving priority to high-power nodes to form transmission paths, network partitioning caused by excessive consumption of low-energy nodes is avoided; for key low-power nodes that cannot be bypassed, a directed charging protocol is triggered, and energy replenishment is implemented using drones or mobile devices to maintain the core node functions; in addition, the routing reconstruction mechanism migrates data to alternative paths in a timely manner when the node power is insufficient, reducing invalid energy loss; the above energy management strategy and routing optimization are deeply coordinated, which not only avoids the blind use of high-energy consumption nodes in traditional redundant transmission, but also repairs energy bottlenecks through active charging mechanisms, achieving balanced distribution and efficient utilization of network energy, and significantly improving the long-term stable operation capability of large-scale sensor networks; (3) Through the parallel transmission of the main path and the redundant path, combined with the slice coding and XOR verification technology, the distributed redundant storage and transmission of data are realized; the receiving end uses the data fusion algorithm to verify and recover the multi-path data. Even if some paths are interfered with and cause data loss or errors, the complete information can still be reconstructed through the data of other paths; the maximum likelihood estimation algorithm ensures that when the main path fails, the redundant data can restore the original content with a high probability, effectively dealing with the uncertainty and interference attacks of the wireless channel; the combination of the above multi-path fault tolerance mechanism and data verification technology breaks through the reliability bottleneck of a single link and forms an information transmission system with strong robustness, which is suitable for industrial monitoring, emergency communication and other scenarios with strict requirements on data integrity. BRIEF DESCRIPTION OF THE DRAWINGS

[0016] The present invention will be further described below with reference to the accompanying drawings.

[0017] Figure 1 A diagram showing the steps of the method of the present invention. DETAILED DESCRIPTION

[0018] The following will clearly and completely describe the technical solutions in the embodiments of the present invention in conjunction with the accompanying drawings. Obviously, the described embodiments are only part of the embodiments of the present invention, not all of the embodiments. Based on the embodiments of the present invention, all other embodiments obtained by ordinary technicians in this field without making any creative efforts shall fall within the scope of protection of the present invention.

[0019] See also Figure 1 As shown, the present invention is an anti-interference secure transmission method for a wireless sensor network, comprising the following steps: Step S1: Real-time acquisition of the remaining power, location information, and communication quality parameters of each sensor node. The remaining power is acquired in real time through the node's built-in power monitoring module, such as ADC sampling. GPS or RSSI triangulation is used to obtain location information. Communication quality parameters such as BER, RSSI, and CCA are collected through the physical layer radio frequency chip. Step S2: When sending data from the source sensor node, a multi-hop routing path is dynamically selected based on the real-time interference detection results, where: When selecting a path, sensor nodes with a remaining battery power lower than a preset threshold are excluded as relay nodes; The sensor nodes that are ranked in the top X in descending order of remaining power and are located in a low-interference area are preferentially selected to form the main transmission path; the low-interference area is obtained by the following method: The node periodically samples the channel idle rate CCA, bit error rate BER, and signal strength fluctuation value F, and calculates the variance or root mean square error RMSE of the RSSI sequence as F; ; like ≥ , it is determined to be a high interference area; if < , determined as a low interference area; If the BER rises by 50% within three consecutive cycles and the signal strength variance exceeds the threshold, it is determined to be under active jamming attack; For example: the preset threshold is 20% of the node's initial power, excluding nodes with power less than 20%; the top 5 low-interference nodes are selected in descending order of remaining power ( < =0.5) to form the main path; Step S3: During redundant transmission, at least two independent redundant paths are generated based on the remaining power distribution of sensor nodes and the interference intensity, and the remaining power of all relay nodes in the redundant paths is higher than a preset threshold. For example, two redundant paths are generated, the power of relay nodes is greater than 30%, and there is no node overlap between the paths and the main path. Step S4: During data transmission, the remaining power of relay nodes is monitored in real time. If the remaining power of at least one sensor node drops below a preset threshold, a dynamic routing reconstruction mechanism is triggered to reselect a new path and migrate data to the new path. For example, the node power is monitored every 500ms, with a threshold set at 25%. When a reconstruction is triggered, an alternative node is preferentially searched for within the neighborhood (within a communication radius of 50 meters). Step S5: After the converged sensor node receives the data from the primary and redundant paths, it recovers the complete information through data fusion and verification algorithms. An XOR checksum (e.g., CRC-16) is used to verify the data, and a maximum likelihood estimation algorithm is implemented based on a Gaussian noise model. In this embodiment, low-battery nodes are eliminated in real time to avoid path interruptions caused by node power outages and improve network connectivity. High-battery and low-interference nodes are selected as the main path to reduce the impact of interference on transmission and lower the bit error rate. At least two independent redundant paths are generated. Even if the main path is interfered with or the node fails, data can still be restored through the redundant path, thereby improving transmission reliability. The path is dynamically adjusted based on the power level and interference intensity to balance the network load and extend the node life cycle.

[0020] The step S2 of dynamically selecting a multi-hop routing path further includes: A comprehensive scoring model is used to score each path. The scoring factors include the remaining battery power of the sensor node, the historical packet loss rate, the current interference intensity and the number of hops. Arrange each path in descending order according to the score, where the path ranked first is the main path and the path ranked second is the redundant candidate path.

[0021] Example: Calculate the comprehensive score for all feasible paths , the path with the highest score is taken as the main path, and the second highest score is taken as the redundant candidate path.

[0022] In this embodiment, multi-dimensional path evaluation is used to integrate power consumption, interference, reliability, namely historical packet loss rate and number of hops, to avoid the limitations of a single indicator and improve the accuracy of path selection; redundant candidate paths are pre-stored, and the path switching time during sudden interference is shortened by using the suboptimal path as a redundant candidate; interference sensitivity sorting is performed, and the average interference intensity of the main path is reduced by giving priority to paths with low interference intensity, significantly improving transmission stability.

[0023] The expression of the comprehensive scoring model is: ; ; in, 、 、 、 is the adjustment coefficient, =1.5, =3, =2, =10, For the The rating of sensor nodes, For the The remaining power of each sensor node, For the The current interference strength of each sensor node, is the interference intensity threshold, is the baseline reliability coefficient, No. The historical reliability coefficient of each sensor node is calculated as follows: ; is the number of path hops, is the maximum allowed number of hops, is the delay coefficient, is the end-to-end delay coefficient, , is the processing delay of the current sensor node, is the waiting time of the data packet in the current sensor node buffer queue, is the wireless transmission delay of the current sensor node, based on the signal rate.

[0024] In this embodiment, the power sensitive weighting is: Amplify the score of high-power nodes and guide routing to prioritize high-energy nodes. For example, the score of a node with 80% power is 60% higher than that of a node with 50% power, delaying the consumption of low-power nodes. Nonlinear interference suppression: using 、 Implement exponential penalties on high-interference nodes, such as when the score approaches 0, to ensure that the interference intensity of the main path is lower than 70% of the interference intensity threshold; Penalize long delay paths to shorten end-to-end delay.

[0025] The redundant path generation in step S3 adopts the following strategy: Through the non-intersecting path algorithm in graph theory, m paths are found as redundant paths in the network topology that excludes sensor nodes with remaining power lower than a preset threshold, and m ≥ 2. The redundant paths meet the following requirements: the total interference intensity is less than the interference intensity threshold, and they are in the first m positions after being sorted in ascending order; for example: Graph theory algorithm: Use the improved Dijkstra algorithm to find two edge-non-intersecting paths, excluding nodes with power < 25% in the network topology.

[0026] Redundant data packets use fragmentation encoding technology to ensure that the original data can be restored if any two paths are successfully transmitted. For example, the original data can be divided into four fragments and encoded using RS(4,2) erasure coding. The data can be restored if any two paths are successfully transmitted.

[0027] In this embodiment, the influence of the same interference source can be avoided by using physically disjoint paths. For example, within the active interference range of 50 meters, interference is independent when the distance between two paths is greater than 100 meters, improving redundancy reliability. Sliced ​​coding fault tolerance: Using RS(4,2) erasure code, data can be recovered with only two successful paths, saving bandwidth resources compared to traditional retransmission mechanisms. By ensuring that the sum of the interference strength of each redundant path is less than the interference strength threshold, the packet error rate of redundant transmission is reduced.

[0028] The method further comprises: Step S6: For key nodes whose remaining power is continuously lower than a preset threshold and cannot be bypassed by routing, a charging request protocol is triggered, and directed energy replenishment is performed through drones or mobile charging devices.

[0029] Example: Critical node determination: If the node power level is continuously less than 15% and it is located at the relay position of at least three paths, a charging request is triggered.

[0030] Charging execution: The coordinate information is sent to the base station via the Zigbee protocol. The base station dispatches the drone (2 hours of flight time, 5W charging power) to arrive within 30 minutes and uses electromagnetic induction charging (charging efficiency 80%).

[0031] In this embodiment, targeted charging is implemented for low-power nodes that cannot be bypassed, such as hub nodes, to avoid network partitioning caused by single point failures and ensure the survival of key nodes. The drone responds to the charging request within 30 minutes, and a single charge can restore the node's power to more than 70%, maintaining continuous operation for 48 hours, improving energy replenishment efficiency. The generation of the independent redundant path meets the following conditions: The redundant path and the main transmission path do not intersect in physical space, and the relay node set does not overlap with the main path; The sum of the interference strengths of redundant paths Both are less than the interference intensity threshold , where the calculation formula for the total interference intensity is: , The redundant path The current interference strength of relay nodes, is the number of redundant path hops.

[0032] For example: Physical non-intersection verification: calculate the Euclidean distance through the node coordinates, and the distance between the relay nodes of the path is greater than 100 meters, which is considered to be physically non-intersection; interference sum calculation: if a redundant path contains 3 nodes, =0.2, =0.3, =0.2, then =0.7<0.8, meeting the conditions.

[0033] In this embodiment, the relay nodes are non-overlapping and physically non-intersecting, ensuring that the interference events of the main path and the redundant path are independent, thereby achieving interference isolation; Constraints make the overall interference intensity of redundant paths controllable and improve the success rate of data recovery.

[0034] When it is detected that the remaining power of the relay node is lower than the preset threshold, the local route discovery protocol is triggered to search for an alternative node in the neighborhood of the current path whose remaining power is higher than the threshold and whose interference strength is lower than the interference strength threshold; If there is no available alternative node in the neighborhood, global routing reconstruction is initiated, and the primary path and redundant path are recalculated based on the current network topology to ensure that the comprehensive score of the new path does not decrease by more than X% of the original path, where X% is 30%.

[0035] Example: Local route discovery: Broadcast RREQ packets within the communication radius of the current node (50 meters) to find nodes with power > 30% and Global reconstruction condition: If no replacement node is found within 30 seconds, the Floyd-Warshall algorithm is used to recalculate the path, requiring the new path score to be ≥ 70% of the original path (X% = 30%).

[0036] In this embodiment, searching for an alternative node within the neighborhood (50-meter radius) takes less than 50ms, which is 10 times faster than global reconstruction, reducing data interruption time and achieving local rapid repair. By limiting the new path score drop to ≤30%, performance degradation caused by blind reconstruction is avoided, achieving reconstruction quality assurance. Local repair is prioritized, and global reconstruction is performed after failure, reducing computing overhead and implementing a hierarchical response strategy.

[0037] The data fusion and verification algorithm in step S5 adopts the following strategy: Perform an XOR check on data packets on the primary and redundant paths, using the checksum to identify data packet damage caused by transmission errors or interference. For example, XOR check is implemented by appending a 16-bit CRC checksum to each data packet. The receiver calculates the checksum and compares it with the transmitted value. When the primary path data is lost or erroneous, the redundant path data is used to restore the original information through the maximum likelihood estimation algorithm. The recovery success rate must meet the following requirements: Where, The number of valid data packets on the main path, is the number of valid data packets on the redundant path, is the recovery efficiency coefficient.

[0038] In this embodiment, the XOR check (CRC-16) can identify 99.9% of single-bit errors and promptly detect data damage caused by interference; the maximum likelihood algorithm uses redundant path data and can still recover the original information with a success rate of more than 95% when the main path packet loss rate reaches 30%, achieving efficient data recovery; Ensure that, as the number of redundant packets increases, the recovery success rate approaches 1.

[0039] For example: Take a 100-node mesh network as an example: Main path selection: Node A (power 90%, =0.2) → Node B (battery 85%, =0.3) → sink node, hop count D=2, score =0.89.

[0040] Redundant path generation: Find path 1 (node ​​C → node D) through the disjoint path algorithm = 0.5) and path 2 (node ​​E → node F, =0.6).

[0041] When the power of node B drops to 20%, a local reconstruction is triggered and an alternative node G (power 75%, =0.4), the new path score is 0.82 (92% of the original path), which meets the requirements.

[0042] It should be noted that the calculation formulas and various parameters involved in the calculations in the present invention have been dimensionally processed in advance, and the process of dimensionless processing is well known in the industry and will not be described here.

[0043] The above is a detailed description of an embodiment of the present invention. However, the content described is only a preferred embodiment of the present invention and should not be considered to limit the scope of the present invention. All equivalent changes and improvements made within the scope of the present invention should still fall within the scope of the patent coverage of the present invention.

Claims

1. A method for anti-interference secure transmission in a wireless sensor network, characterized in that: The following steps are involved: Step S1: Acquire the remaining power, location information and communication quality parameters of each sensor node in real time; Step S2: When sending data from the source sensor node, a multi-hop routing path is dynamically selected based on the real-time interference detection results, where: When selecting a path, sensor nodes with a remaining battery power lower than a preset threshold are excluded as relay nodes; The sensor nodes that are ranked in the top X in descending order of remaining power and are located in low-interference areas are preferentially selected to form the main transmission path; Step S3: During redundant transmission, at least two independent redundant paths are generated based on the remaining power distribution of the sensor nodes and the interference intensity, and the remaining power of all relay nodes in the redundant paths is higher than a preset threshold; Step S4: During data transmission, the remaining power of the relay nodes is monitored in real time. If the remaining power of at least one sensor node drops below a preset threshold, the dynamic routing reconstruction mechanism is triggered to reselect the path and migrate the data to the new path. Step S5: After the convergent sensor node receives the primary path and redundant path data, it restores the complete information through data fusion and verification algorithms.

2. The anti-interference secure transmission method for wireless sensor networks according to claim 1, characterized in that: The step S2 of dynamically selecting a multi-hop routing path further includes: A comprehensive scoring model is used to score each path. The scoring factors include the remaining battery power of the sensor node, the historical packet loss rate, the current interference intensity and the number of hops. Arrange each path in descending order according to the score, where the path ranked first is the main path and the path ranked second is the redundant candidate path.

3. The anti-interference secure transmission method for wireless sensor networks according to claim 2, characterized in that: The expression of the comprehensive scoring model is: ； ； in, 、 、 、 is the adjustment coefficient, For the The rating of sensor nodes, For the The remaining power of each sensor node, For the The current interference strength of each sensor node, is the interference intensity threshold, is the baseline reliability coefficient, No. The historical reliability coefficient of each sensor node is calculated as follows: ; is the number of path hops, is the maximum allowed number of hops, is the delay coefficient, is the end-to-end delay coefficient, , is the processing delay of the current sensor node, is the waiting time of the data packet in the current sensor node buffer queue, is the wireless transmission delay of the current sensor node.

4. The anti-interference secure transmission method for wireless sensor networks according to claim 1, characterized in that: The redundant path generation in step S3 adopts the following strategy: Using the disjoint path algorithm in graph theory, we search for m paths as redundant paths in the network topology, excluding sensor nodes whose remaining battery power is lower than a preset threshold, where m ≥ 2. The redundant paths satisfy the following conditions: the sum of the interference strength is less than the interference strength threshold, and they are in the first m positions after being sorted in ascending order. Redundant data packets use fragmentation encoding technology to ensure that the original data can be restored if any two paths are successfully transmitted.

5. The anti-interference secure transmission method for wireless sensor networks according to claim 1, characterized in that: The method further comprises: Step S6: For key nodes whose remaining power is continuously lower than a preset threshold and cannot be bypassed by routing, a charging request protocol is triggered, and directed energy replenishment is performed through drones or mobile charging devices.

6. The anti-interference secure transmission method for wireless sensor networks according to claim 1, characterized in that: The generation of the independent redundant path meets the following conditions: The redundant path and the main transmission path do not intersect in physical space, and the relay node set does not overlap with the main path; The sum of the interference strengths of redundant paths Both are less than the interference intensity threshold , where the calculation formula for the total interference intensity is: , The redundant path The current interference strength of relay nodes, is the number of redundant path hops.

7. The anti-interference secure transmission method for wireless sensor networks according to claim 1, characterized in that: When it is detected that the remaining power of the relay node is lower than the preset threshold, the local route discovery protocol is triggered to search for an alternative node in the neighborhood of the current path whose remaining power is higher than the threshold and whose interference strength is lower than the interference strength threshold; If there is no available alternative node in the neighborhood, global routing reconstruction is initiated, and the primary path and redundant path are recalculated based on the current network topology to ensure that the comprehensive score of the new path does not decrease by more than X% of the original path, where X% is 30%.

8. The anti-interference secure transmission method for wireless sensor networks according to claim 1, characterized in that: The data fusion and verification algorithm in step S5 adopts the following strategy: Perform XOR check on data packets on the primary and redundant paths, and use the checksum to identify data packet damage caused by transmission errors or interference; When the primary path data is lost or erroneous, the redundant path data is used to restore the original information through the maximum likelihood estimation algorithm. The recovery success rate must meet the following requirements: Where, The number of valid data packets on the main path, is the number of valid data packets on the redundant path, is the recovery efficiency coefficient.

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