A wireless sensor network distributed security positioning method, device and equipment

Abstract

The application discloses a wireless sensor network distributed security positioning method, device and equipment, and relates to the technical field of wireless sensor networks. The application receives two groups of encrypted positioning information of sensors in a triangular neighbor set for each non-anchor node, and the two groups of encrypted positioning information are encrypted by two different keys, so that the non-anchor node can decrypt and compare to determine whether the angle measurement information and the position estimation value sent by the sensors in the triangular neighbor set are safe, thereby establishing a trust degree evaluation for the sensors in the triangular neighbor set, and then determining the dynamic barycentric coordinates of the non-anchor node after the weighted fusion of the triangular neighbor set based on the trusted triangular neighbor set, and determining the position estimation value of the non-anchor node in combination with the decrypted position estimation value of the sensors in the trusted triangular neighbor set, thereby improving the security and reliability of the wireless sensor network distributed positioning.

Description

Technical Field

[0001] This invention relates to the field of wireless sensor network technology, and in particular to a distributed secure positioning method, apparatus, and device for wireless sensor networks. Background Technology

[0002] Currently, wireless sensor networks (WSNs) are network systems composed of numerous low-power, miniature sensors. By deploying a large number of sensors, wide-area real-time monitoring and data acquisition can be achieved. This technology is widely used in civilian, military, and industrial fields, such as target tracking, smart homes, smart cities, collaborative transportation, and the Internet of Things (IoT). In these practical application scenarios, a lack of sensor location data can hinder collaboration and affect the efficiency and adaptability of overall work execution. Therefore, obtaining real-world location data is crucial for most applications in wireless sensor networks.

[0003] In existing technologies, wireless sensor networks employ both centralized and distributed positioning methods. Centralized positioning typically requires a central sensor to collect all measurement information and communicate with all other sensors. However, as network size increases, the computational complexity and communication load of the central sensor grow exponentially, significantly reducing system reliability. In contrast, distributed positioning relies on each sensor for computation. Non-anchor node sensors, lacking their own location information, can locate themselves using distance, orientation, or angle measurements from neighboring nodes. Even when some sensors are attacked or malfunction, data from other sensors can still be used to calculate accurate location estimates, thus exhibiting better robustness.

[0004] However, in existing sensor networks, distributed positioning is sensitive and highly vulnerable to network attacks due to its open distributed wireless network communication. It is very likely to suffer from complex network attacks, which greatly reduces the security and reliability of distributed positioning in wireless sensor networks. Summary of the Invention

[0005] Therefore, it is necessary to provide a distributed secure positioning method, apparatus, and device for wireless sensor networks to address the aforementioned technical problems.

[0006] The present invention adopts the following technical solution:

[0007] This invention provides a distributed secure positioning method for wireless sensor networks, comprising:

[0008] In a wireless sensor network, each sensor that does not have its own location information is considered a non-anchor node. For each non-anchor node, several triangular neighbor sets formed by the neighboring sensors of each non-anchor node are determined.

[0009] The non-anchor node receives two sets of encrypted positioning information from the centralized sensors of each triangular neighbor; the two sets of encrypted positioning information are encrypted with two different keys; each set of encrypted positioning information includes angle measurement information and position estimate;

[0010] The two sets of encrypted positioning information of the sensors in each triangular neighbor set are decrypted by the non-anchor node. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy.

[0011] Based on the centroid coordinates obtained from the angle measurement information of the trusted triangular neighbor set sensors, determine the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set.

[0012] The position estimate of the non-anchor node is determined based on the decrypted position estimate corresponding to the sensor in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set.

[0013] Optionally, the two sets of encrypted location information are encrypted using two different keys, specifically including:

[0014] The angle measurement information and position estimate are encrypted using the following formula:

[0015]

[0016] in, Indicates encryptor I, This represents encryptor II, where 'a' is a parameter in encryptor I and 'c' is a parameter in encryptor II. This indicates that at time t, neighbor node j of non-anchor node i wants to send the k-th type of plaintext information to non-anchor node i. This indicates that the k-th encrypted message that non-anchor node i's neighbor node j needs to send to non-anchor node i at time t, after being encrypted by encryptor I. This indicates that the k-th encrypted message that non-anchor node i's neighbor node j, after being encrypted by encryptor II, needs to be sent to non-anchor node i at time t.

[0017] Optionally, the step of decrypting the two sets of encrypted positioning information of the triangular neighbor sensors through the non-anchor node specifically includes:

[0018] The non-anchor node decrypts the two sets of encrypted positioning information from the sensors in each triangular neighbor cluster according to the following formula:

[0019]

[0020] in, and These represent decryptor I and decryptor II, respectively.

[0021] Optionally, the step of determining that the corresponding triangular neighbor set is trustworthy when the two sets of angle measurement information and position estimates obtained by each sensor in the triangular neighbor set are the same specifically includes:

[0022] For each triangular neighbor set of the non-anchor point, the corresponding sensor is considered trustworthy when the two sets of angle measurement information and position estimates obtained by each sensor in the triangular neighbor set satisfy the following formula:

[0023]

[0024] If all sensors in the triangular neighbor set are trustworthy, the trust level of the triangular neighbor set is determined to be 1; otherwise, the trust level of the triangular neighbor set is determined to be 0.

[0025] Optionally, the dynamic centroid coordinates of the non-anchor node in the weighted fusion of each triangular neighbor set can be determined using the following formula, based on the centroid coordinates obtained from the angle measurements of the sensors in the trusted triangular neighbor set:

[0026]

[0027] in, Let be the set of all neighbor nodes in each triangular neighbor set of non-anchor node i, and s be the set of... For any neighboring node, a is (t) represents the dynamic centroid coordinates of non-anchor node i after weighted fusion of the triangular neighbor sets containing neighbor node s. Let be the centroid coordinates of the non-anchor node i in the triangular neighbor set r corresponding to the neighbor node s. For the trust level weighted average of the triangular neighbor set r, η i (t) represents the total trust level of each triangular neighbor set of non-anchor node i, and q represents the number of triangular neighbor sets of non-anchor node i.

[0028] Optionally, the position estimate of the non-anchor node can be determined by the following formula based on the decrypted position estimate corresponding to the sensors in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set:

[0029]

[0030] Where, p i (t+1) is the estimated position of non-anchor node i at time t+1, p i (t) represents the estimated position of the non-anchor node i at time t, γ is the update weighting constant, and p s (t) represents the decrypted position estimate of the neighbor node s of the non-anchor node i.

[0031] This invention provides a distributed secure positioning device for wireless sensor networks, comprising:

[0032] The neighbor determination module is used to treat each sensor in the wireless sensor network that does not have its own location information as a non-anchor node, and for each non-anchor node, determine several triangular neighbor sets formed by the neighbor sensors of each non-anchor node.

[0033] The encrypted transmission module is used to receive two sets of encrypted positioning information from the centralized sensors of each triangular neighbor through the non-anchor node; the two sets of encrypted positioning information are encrypted with two different keys; each set of encrypted positioning information includes angle measurement information and position estimation value.

[0034] The decryption judgment module is used to decrypt the two sets of encrypted positioning information of the sensors in each triangular neighbor set through the non-anchor node. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy.

[0035] The centroid coordinate determination module is used to determine the dynamic centroid coordinates of the non-anchor node after weighted fusion of the triangular neighbor sets, based on the centroid coordinates obtained from the angle measurement information of the sensors in the trusted triangular neighbor set.

[0036] The positioning module is used to determine the position estimate of the non-anchor node based on the decrypted position estimate corresponding to the sensors in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set.

[0037] The present invention provides a computer-readable storage medium storing a computer program that, when executed by a processor, implements the above-described distributed secure positioning method for wireless sensor networks.

[0038] The present invention provides a computer device, including a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor executes the program to implement the above-described distributed secure positioning method for wireless sensor networks.

[0039] The above-mentioned at least one technical solution adopted in this invention can achieve the following beneficial effects:

[0040] To address complex network attacks, this invention, in distributed positioning within a wireless sensor network, receives two sets of encrypted positioning information from sensors in its triangular neighbor set for each non-anchor node. These two sets of encrypted positioning information are encrypted using two different keys, allowing the non-anchor node to decrypt and compare them. If the comparison matches, the data has not been tampered with and can be trusted for subsequent calculations of the non-anchor node's dynamic centroid coordinates in each triangular neighbor set. Otherwise, the data has been tampered with and is untrustworthy. The dynamic centroid coordinates of the non-anchor node can then be determined by weighting the centroid coordinates obtained from the trusted triangular neighbor set with a trust level. Combined with the decrypted position estimates from the trusted triangular neighbor set sensors, the position estimate of the non-anchor node is then determined.

[0041] This invention employs two different keys for symmetric encryption during the transmission of positioning information between non-anchor node sensors and their triangular neighbor sensors. The non-anchor node sensors can accurately determine whether the positioning information received by the non-anchor node from each triangular neighbor sensor is secure by comparing the two decryption results. This establishes a trust assessment for each triangular neighbor sensor and performs positioning only based on the trustworthy parts, thereby improving the security and reliability of distributed positioning in wireless sensor networks. Attached Figure Description

[0042] The accompanying drawings, which are included to provide a further understanding of the invention and form part of this invention, illustrate exemplary embodiments of the invention and are used to explain the invention, but do not constitute an undue limitation of the invention. In the drawings:

[0043] Figure 1 A flowchart illustrating a distributed secure positioning method for wireless sensor networks provided by this invention. Figure 1 ;

[0044] Figure 2 A flowchart illustrating a distributed secure positioning method for wireless sensor networks provided by this invention. Figure 2 ;

[0045] Figure 3 The present invention provides a sensor i for measuring angle θ kij A schematic diagram;

[0046] Figure 4 A schematic diagram illustrating a complex network attack provided by the present invention;

[0047] Figure 5 A schematic diagram illustrating the encryption and decryption process provided by this invention;

[0048] Figure 6 A schematic diagram illustrating the privacy protection result of an anti-eavesdropping method provided by the present invention;

[0049] Figure 7 A schematic diagram illustrating the detection results of a deception attack 1 provided by the present invention;

[0050] Figure 8 A schematic diagram illustrating the detection results of a deception attack 2 provided by the present invention;

[0051] Figure 9 This invention provides a schematic diagram of the location estimation and error trajectory obtained by a localization algorithm under complex network attacks.

[0052] Figure 10 This invention provides a schematic diagram of a distributed secure positioning device for a wireless sensor network.

[0053] Figure 11 This is a schematic diagram of a computer device for implementing a distributed secure positioning method for wireless sensor networks, as provided by the present invention. Detailed Implementation

[0054] To make the objectives, technical solutions, and advantages of this invention clearer, the technical solutions of this invention will be clearly and completely described below in conjunction with specific embodiments and corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of this invention, and not all of them. Based on the embodiments of this invention, all other embodiments obtained by those skilled in the art without creative effort are within the scope of protection of this invention.

[0055] Currently, in distributed positioning technology, measurements between sensor nodes typically employ three methods: distance measurement, orientation measurement, and angle measurement. Compared to distance measurement, angle measurement is significantly unaffected by ground inhomogeneity and multipath effects, thus providing more reliable measurement data in complex environments. Furthermore, unlike orientation measurement, angle measurement does not require establishing a unified coordinate system or handling coordinate transformations between different local coordinate systems. Therefore, this invention employs angle measurement for inter-sensor observation.

[0056] The technical solutions provided by the various embodiments of the present invention will be described in detail below with reference to the accompanying drawings.

[0057] Figure 1 This is a schematic flowchart of a distributed secure positioning method for wireless sensor networks according to the present invention. Figure 1 Specifically, it includes the following steps:

[0058] S101: Treat each sensor in the wireless sensor network that does not have its own location information as a non-anchor node, and for each non-anchor node, determine several triangular neighbor sets formed by the neighbor sensors of each non-anchor node.

[0059] S102: Receive two sets of encrypted positioning information from the centralized sensors of each triangular neighbor through the non-anchor node; the two sets of encrypted positioning information are encrypted with two different keys; each set of encrypted positioning information includes angle measurement information and position estimate.

[0060] S103: Decrypt the two sets of encrypted positioning information of the sensors in each triangular neighbor set through the non-anchor node. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy.

[0061] S104: Determine the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set based on the centroid coordinates obtained from the angle measurement information of the trusted triangular neighbor set sensors.

[0062] S105: Determine the position estimate of the non-anchor node based on the decrypted position estimate corresponding to the sensor in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set.

[0063] For ease of explanation, the following description focuses solely on the server as the executing entity. The server mentioned in this invention can be a server set up on a business platform, or a device such as a desktop computer or laptop computer capable of executing the solution of this invention.

[0064] To address complex network attacks (eavesdropping, DoS attacks, spoofing attacks, etc.), existing positioning methods cannot guarantee the privacy and security of transmitted data or the accuracy of positioning. This invention proposes an angle-based distributed secure positioning method for two-dimensional wireless sensor networks under complex network attacks, enabling precise positioning of wireless sensor networks even under such conditions. For details, please refer to... Figure 2 , Figure 2 This is a schematic flowchart of a distributed secure positioning method for wireless sensor networks according to the present invention. Figure 2 .

[0065] When locating each sensor in a wireless sensor network, we can first categorize them into anchor nodes and non-anchor nodes based on whether the sensors know their own location information, according to the established wireless sensor network.

[0066] The sensor network model contains a set of points. Directed graph with edge set ε An edge that starts from node i and ends at node j is represented by an ordered pair (i,j). It is represented as a combination of edge sets ε1 and ε2.

[0067] Consider a wireless sensor network model in two-dimensional Euclidean space, where the sensor set Φ = {1,2,...,n}, and n represents the total number of sensors. Assume the sensor set is divided into a set of anchor nodes Λ = {1,2,3} and a set of non-anchor nodes Ω = {4,5,...,n}, where anchor nodes can be located via GPS (location known), while non-anchor nodes cannot be located via GPS (location unknown). Let n be 10.

[0068] In this embodiment, m represents meters, rad represents radians, and the estimated position of each sensor is defined as p. i (t)=[x i (t),y i [(t)], the actual position is defined as p i =[x i ,y i The actual positions of the sensors are set as follows: p1 = [-2.5m, -2m], p2 = [2.5m, -2m], p3 = [0m, 3m], p4 = [-1.5m, -1m], p5 = [-0.25m, 0.5m], p6 = [0m, -0.5m], p7 = [1.5m, -1m], p8 = [0.25m, 0.5m], p9 = [0m, 0m], p 10 =[0m,2m].

[0069] The initial position estimates of the non-anchor nodes are randomly set as p4(0) = [-1m, -3m], p5(0) = [-0.25m, -0.5m], p6(0) = [2m, 3m], p7(0) = [3m, 0m], p8(0) = [-2m, -2m], p9(0) = [-2m, 1m].

[0070] The neighbor set of non-anchor node 4 is {1,5,6}, the neighbor set of non-anchor node 5 is {4,8,10}, {4,9,10}, {4,6,10}, the neighbor set of non-anchor node 6 is {4,7,9}, {4,5,7}, {4,7,8}, the neighbor set of non-anchor node 7 is {2,6,8}, the neighbor set of non-anchor node 8 is {5,7,10}, {6,7,10}, {9,7,10}, the neighbor set of non-anchor node 9 is {5,6,8}, and the neighbor set of node 10 is {3,5,8}. The error between the true position and the estimated position of non-anchor node i is defined as e. i (t)=||p i -p i (t)||. Set the weight γ = 0.75.

[0071] For GPS-denied areas such as indoors, tunnels, and underwater, sensors can be deployed as anchor nodes outside the GPS signal denial area. The convex hull formed by all anchor nodes covers the entire GPS-denied area, thereby using the positioning algorithm described in this invention to locate all sensors (non-anchor nodes) within the GPS-denied area.

[0072] Then, the distance angle can be measured using LiDAR and a depth camera, and the triangular neighbor set of the sensor node can be determined. For example, the non-anchor node i of the sensor can use LiDAR and a depth camera to measure the angle between its two adjacent sensor nodes j and k, denoted as θ. jik , satisfying θ jik ≤π, such as Figure 3 As shown, Figure 3 A sensor i in this invention measures the angle θ. kij A schematic diagram, Figure 3 The diagram illustrates how a non-anchor node i of a sensor measures the angle between two adjacent sensor nodes j and k within a finite range.

[0073] For each non-anchor node i, find the triangular neighbor set Δ i This is a crucial step in the localization algorithm. Given the deployment density, a non-anchor node i can be assigned an initial communication radius r. i Determine its neighbor set Υ(i,r) i )={j∈Φ:d ij <r i}, then in Υ(i,r i In the first step, select any three neighboring nodes and test whether the node i is located within the convex hull of these three neighbors. If all tests fail, the non-anchor node i adaptively increases its communication radius in small increments. By repeating this process, the triangular neighbor set Δ can be finally determined. i After determining the triangular neighbor set, each non-anchor node i will receive Δ i The information sent by the sensor nodes (including angle measurement information and positioning estimates). The data packets sent by the neighbors of non-anchor node i (denoted as j, k, l) at time t are represented as follows:

[0074] The non-anchor node i can use the received angle measurement information to calculate its relative to Δ. i The centroid coordinates of adjacent nodes.

[0075] Suppose there are four nodes i, j, k, l in a two-dimensional space, and their positions are represented as follows: The position of node i is represented by: p i =a ij p j +a ik p k +a ilp l , where a i. This represents the centroid coordinates, which can be calculated using the following formula:

[0076] Based on the Cayley-Menger determinant, we can derive:

[0077]

[0078] This leads to the formula for calculating the centroid coordinates:

[0079]

[0080] Considering that the triangular neighbor set of non-anchor node i may not be unique, and in the ideal scenario where there is no network attack, assume that non-anchor node i has q triangular neighbor sets, i.e. The set of all nodes in the triangular neighbor set of node i is represented as: To make the barycenter coordinates more accurate, it is necessary to perform an average weighted fusion of the barycenter coordinates under different triangle neighborhoods, that is:

[0081] Furthermore, precise positioning can be achieved through distributed iteration, with node i performing a position estimation and update mechanism:

[0082] The matrix-form position update expression for the entire sensor network is:

[0083] in,

[0084] If sensor i considers both the current position update result and historical time information during iterative localization, then the iterative form can be described as follows:

[0085] Where γ>0 is a weighting constant.

[0086] The matrix-form position update expression for the entire sensor network then becomes: Where D=(1-γ)I n-3 +γC.

[0087] To address complex network attacks, this invention proposes a distributed security location method. These complex network attacks are categorized into three types, such as... Figure 4 As shown, Figure 4 This is a schematic diagram of a complex network attack according to the present invention:

[0088] 1) The first scenario involves an attacker inserting themselves into the communication link, capturing the data being transmitted, and forwarding the original data, leading to privacy breaches. This invention addresses this by designing a symmetric encryption privacy protection scheme, such as... Figure 4 As shown in section (a).

[0089] 2) The second type involves an attacker inserting into the communication link, capturing data being transmitted, and preventing it from being forwarded, thus blocking data transmission and preventing sensor nodes from receiving any information. When a sensor node i cannot receive information from its neighbor node j at time t, it is considered that the communication link from node j to node i has been attacked. Therefore, there is no need to design a special detection strategy for this type of attack, such as... Figure 4 As shown in section (b).

[0090] 3) The third method involves an attacker inserting into the communication link, capturing and modifying the transmitted data, causing the sensor's estimated location to converge to an incorrect position. This invention determines whether an attack has occurred by comparing the results of dual-key encryption and decryption. Figure 4 As shown in section (c).

[0091] For the sender, encrypting the plaintext data packets is a simple and effective data encryption method that can effectively prevent unauthorized eavesdropping and data tampering. Symmetric encryption uses a single key for both encryption and decryption, greatly simplifying key management. Its computation is not only simple but also energy-efficient, requiring minimal computational resources, making it particularly suitable for sensor devices that rely on battery power and have limited resources.

[0092] For each sensor node j∈Δ i When it sends information to node i, an attacker can eavesdrop on the data packets. The invention relates to angle and position information. It proposes a symmetric encryption privacy protection scheme where symmetric encryption uses a single key to encrypt and decrypt two data items. Simultaneously, the sender independently encrypts the same plaintext twice using symmetric encryption, generating two ciphertexts. The receiver decrypts each ciphertext separately and compares the decryption results to determine if the data has been tampered with during transmission. Figure 5 This is a schematic diagram illustrating an encryption and decryption process in this invention. Figure 5 Part (a) illustrates encryption, and part (b) illustrates decryption. The transmitted information is as follows:

[0093] in, and This represents the encrypted information sent by neighbor node j to sensor node i at time t. The plaintext θ... ijk ,θ ijl ,θ kjl ,xj (t),y j (t) is denoted as Cipher Recorded as Cipher Recorded as

[0094] Key generation: Before sending information, a, c∈(1,∞) are selected as keys I and II for all sensors. These keys are not transmitted during data transmission.

[0095] plain text Encrypted into ciphertext The angle measurement information and position estimate can be encrypted using the following formula:

[0096]

[0097] in, Indicates encryptor I, This represents encryptor II, where 'a' is a parameter in encryptor I and 'c' is a parameter in encryptor II. This indicates that at time t, neighbor node j of non-anchor node i wants to send the k-th type of plaintext information to non-anchor node i. This indicates that the k-th encrypted message that non-anchor node i's neighbor node j needs to send to non-anchor node i at time t, after being encrypted by encryptor I. This indicates that the k-th encrypted message that non-anchor node i's neighbor node j, after being encrypted by encryptor II, needs to be sent to non-anchor node i at time t.

[0098] Figure 6 This is a schematic diagram illustrating the privacy protection result of an anti-eavesdropping method in this invention. Figure 6 Part (a) illustrates encryption scheme 1, and part (b) illustrates encryption scheme 2. Both parts compare and analyze the ciphertext obtained by the attacker with the original text before encryption by the sensor node. The horizontal axis represents time or iteration steps, and the vertical axis represents the numerical range.

[0099] The information receiver can decrypt the data packet. Specifically, the non-anchor node can decrypt the encrypted angle measurement information and position estimate of each triangular neighbor set according to the following formula:

[0100]

[0101] in, and These represent decryptor I and decryptor II, respectively.

[0102] This invention determines whether data has been tampered with during transmission by comparing the outputs of two decryption methods. Specifically, for each triangular neighbor set of the non-anchor point, if the two sets of angle measurement information and position estimates obtained by each sensor in the triangular neighbor set satisfy the following formula, the data of the corresponding sensor is considered trustworthy and has not been tampered with; otherwise, it is considered to have been tampered with:

[0103] If all sensors in the triangular neighbor set are trustworthy, the trust level of the triangular neighbor set is determined to be 1; otherwise, the trust level of the triangular neighbor set is determined to be 0.

[0104] Figure 7 This is a schematic diagram of the detection results of a deception attack 1 in this invention. Figure 7 The simulated attack type is direct tampering with transmitted information. The horizontal axis represents the time or sensor location iteration steps, and the vertical axis represents the attack status, with 0 indicating no attack and 1 indicating an attack. Figure 7 The distribution of detected attack times was compared with the distribution of actual attack times to demonstrate the effectiveness of the invention.

[0105] Figure 8 This is a schematic diagram illustrating the detection results of a deception attack 2 in this invention. Figure 7 The simulated attack type in the diagram is sending intercepted transmission information. The horizontal axis represents the time or sensor location iteration steps, and the vertical axis represents the attack status, with 0 indicating no attack and 1 indicating an attack. Figure 8 The distribution of detected attack times was compared with the distribution of actual attack times to demonstrate the effectiveness of the invention.

[0106] Subsequently, a weighted fusion of the centroid coordinates can be performed based on a trust assessment mechanism. This trust assessment mechanism is a quantitative tool used to evaluate the trustworthiness of communications, data, and participants in fields such as cybersecurity, social networks, and sensor networks. It collects and analyzes various indicators to determine the level of trust that a system or user can rely on when facing uncertainty and potential risks, thereby helping to make more informed decisions.

[0107] The set of all triangular neighbors of sensor non-anchor node i It can be divided into two categories, Γ i (t) and Θ i (t). Θ i (t) represents the triangular neighbor set that has not been subjected to complex network attacks; Γ i (t) represents the triangular neighbor set subjected to a complex network attack. The total trust score of each triangular neighbor set of non-anchor node i is denoted as:

[0108] in, The triangular neighbor set of non-anchor node i The corresponding sub-trust level, hour hour If the trust level η i (t) = 0, indicating that the information received by the non-anchor node i of the sensor is completely unreliable, and the non-anchor node i of the sensor will keep its current position estimate unchanged.

[0109] Sensor non-anchor node i relative to a triangular neighbor set The dynamic centroid coordinates are:

[0110] Sensor i relative to all triangular neighbor sets The weighted dynamic centroid coordinates, or the dynamic centroid coordinates of non-anchor node i after weighted fusion of the triangular neighbor sets containing neighbor node s, are:

[0111] For distributed location under complex network attacks, for any non-anchor node i∈Ω, the location iteration formula in a complex network attack environment is:

[0112] In the formula, p i (t+1) is the estimated position of non-anchor node i at time t+1, p i (t) represents the estimated position of the non-anchor node i at time t, γ is the update weighting constant, and p s (t) represents the decrypted position estimate of the neighbor node s of the non-anchor node i.

[0113] When the reliability η of sensor i i When (t) > 0, even if there are risks in the communication environment, the location estimate can still be inferred at the next time t+1. However, if the confidence level η i If (t) = 0, it means that the information received by sensor i is completely unreliable. Therefore, sensor i will keep its current position estimate unchanged until the confidence level is greater than zero at a subsequent time, at which point the position estimate will be updated.

[0114] Figure 9 This is a schematic diagram of the location estimation and error trajectory obtained by a localization algorithm under complex network attacks in this invention. Figure 9 Part (a) shows the position estimation trajectory, with the horizontal axis corresponding to the x-axis and the vertical axis corresponding to the y-axis. Part (b) shows the positioning error trajectory, with the horizontal axis representing time or iteration steps, the vertical axis representing different sensor non-anchor nodes, and the vertical axis representing the positioning error value. It can be seen that even under complex network attacks, as the number of iteration steps increases, the positioning errors of each sensor non-anchor node converge to the effective range.

[0115] based on Figure 1 The distributed secure positioning method for wireless sensor networks, as shown in this invention, addresses complex network attacks. In distributed positioning within a wireless sensor network, for each non-anchor node, it receives two sets of encrypted positioning information from sensors in its triangular neighbor set. These two sets of encrypted positioning information are encrypted using two different keys, allowing the non-anchor node to decrypt and compare them. If the comparisons match, it indicates that the data has not been tampered with and can be trusted for subsequent calculations of the dynamic centroid coordinates of the non-anchor node in each triangular neighbor set. Otherwise, it indicates that the data has been tampered with and cannot be trusted. Subsequently, the dynamic centroid coordinates of the non-anchor node can be determined by weighting the centroid coordinates obtained from the trusted triangular neighbor set with a trust level. Combined with the decrypted position estimates corresponding to the sensors in the trusted triangular neighbor set, the position estimate of the non-anchor node can be determined.

[0116] This invention employs two different keys for symmetric encryption during the transmission of positioning information between non-anchor node sensors and their triangular neighbor sensors. The non-anchor node sensors can accurately determine whether the positioning information received by the non-anchor node from each triangular neighbor sensor is secure by comparing the two decryption results. This establishes a trust assessment for each triangular neighbor sensor and performs positioning only based on the trustworthy parts, thereby improving the security and reliability of distributed positioning in wireless sensor networks.

[0117] The sensor network localization method proposed in this invention is angle-distributed only, requiring only a small amount of online computation to achieve localization of the entire sensor network, thus avoiding the risk of energy loss. Furthermore, since angle-distributed localization can fully utilize the historical location information of neighboring nodes, it requires only a small number of anchor points and exhibits better robustness compared to centralized localization methods, making it suitable for complex localization environments.

[0118] The key used in this invention is not transmitted, preventing privacy leaks. This invention uses symmetric encryption, allowing us to predict whether data has been tampered with. Symmetric encryption greatly simplifies the key management process. Its computation is not only simple but also has low power consumption and minimal computational resource requirements, making it particularly suitable for battery-powered sensor devices with limited resources.

[0119] This invention utilizes a trust assessment strategy to achieve precise location of non-anchor nodes. A trust assessment mechanism is a quantitative tool used to evaluate the trust level of communications, data, and participants in fields such as cybersecurity, social networks, and sensor networks. It collects and analyzes various indicators to determine the level of trust that a system or user can rely on when facing uncertainty and potential risks, thereby assisting in making more informed decisions.

[0120] When applying the distributed secure positioning method for wireless sensor networks provided by this invention, it is not necessary to... Figure 1 The steps shown are executed in sequence. The specific execution order of each step can be determined as needed, and this invention does not impose any restrictions on it.

[0121] The above describes a distributed secure positioning method for wireless sensor networks provided by one or more embodiments of the present invention. Based on the same idea, the present invention also provides a corresponding distributed secure positioning device for wireless sensor networks, such as... Figure 10 As shown.

[0122] Figure 10 A schematic diagram of a distributed secure positioning device for a wireless sensor network provided by the present invention includes:

[0123] The neighbor determination module 201 is used to treat each sensor in the wireless sensor network that does not have its own location information as a non-anchor node, and for each non-anchor node, determine several triangular neighbor sets formed by the neighbor sensors of each non-anchor node.

[0124] The encrypted transmission module 202 is used to receive two sets of encrypted positioning information from the centralized sensors of each triangular neighbor through the non-anchor node; the two sets of encrypted positioning information are encrypted with two different keys; each set of encrypted positioning information includes angle measurement information and position estimation value.

[0125] The decryption judgment module 203 is used to decrypt the two sets of encrypted positioning information of the sensors in each triangular neighbor set through the non-anchor node. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy.

[0126] The centroid coordinate determination module 204 is used to determine the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set based on the centroid coordinates obtained from the angle measurement information of the sensors in the trusted triangular neighbor set.

[0127] The positioning module 205 is used to determine the position estimate of the non-anchor node based on the decrypted position estimate corresponding to the sensors in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set.

[0128] Specific limitations regarding the distributed secure positioning device for wireless sensor networks can be found in the limitations of the distributed secure positioning method for wireless sensor networks described above, and will not be repeated here. Each module in the aforementioned distributed secure positioning device for wireless sensor networks can be implemented entirely or partially through software, hardware, or a combination thereof. These modules can be embedded in or independent of the processor in a computer device in hardware form, or stored in the memory of a computer device in software form, so that the processor can call and execute the corresponding operations of each module.

[0129] The present invention also provides a computer-readable storage medium storing a computer program that can be used to execute the above-described... Figure 1 A distributed secure positioning method for wireless sensor networks is provided.

[0130] The present invention also provides Figure 11 The schematic diagram of the computer device shown is as follows: Figure 11 As shown, at the hardware level, this computer device includes a processor, internal bus, network interface, memory, and non-volatile memory, and may also include other hardware required for business operations. The processor reads the corresponding computer program from the non-volatile memory into memory and then executes it to achieve the above. Figure 1 A distributed secure positioning method for wireless sensor networks is provided.

[0131] Those skilled in the art will understand that all or part of the processes in the methods of the above embodiments can be implemented by a computer program instructing related hardware. The computer program can be stored in a non-volatile computer-readable storage medium, and when executed, it can include the processes of the embodiments of the methods described above. Any references to memory, storage, databases, or other media used in the embodiments provided by this invention can include at least one of non-volatile and volatile memory. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical storage, etc. Volatile memory can include random access memory (RAM) or external cache memory. By way of illustration and not limitation, RAM can be in various forms, such as static random access memory (SRAM) or dynamic random access memory (DRAM), etc.

[0132] The technical features of the above embodiments can be combined in any way. For the sake of brevity, not all possible combinations of the technical features in the above embodiments are described. However, as long as there is no contradiction in the combination of these technical features, they should be considered to be within the scope of this invention.

Claims

1. A distributed secure positioning method for wireless sensor networks, characterized in that, include: In a wireless sensor network, each sensor that does not have its own location information is considered a non-anchor node. For each non-anchor node, several triangular neighbor sets formed by the neighboring sensors of each non-anchor node are determined. The non-anchor node receives two sets of encrypted positioning information from the centralized sensors of each triangular neighbor; the two sets of encrypted positioning information are encrypted with two different keys; each set of encrypted positioning information includes angle measurement information and position estimate; The two sets of encrypted positioning information of the sensors in each triangular neighbor set are decrypted by the non-anchor node. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy. Based on the centroid coordinates obtained from the angle measurement information of the trusted triangular neighbor set sensors, determine the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set. The position estimate of the non-anchor node is determined based on the decrypted position estimate corresponding to the sensor in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set. The two sets of encrypted location information are encrypted using two different keys, specifically including: The angle measurement information and position estimate are encrypted using the following formula: in, Indicates encryptor I, Indicates Encryptor II, c is a parameter in encryptor I, and c is a parameter in encryptor II. Indicates non-anchor nodes i neighboring nodes j exist t It must be sent to non-anchor nodes at all times. i The k Plaintext information, This indicates the non-anchor node after encryption by encryptor I. i neighboring nodes j exist t It must be sent to non-anchor nodes at all times. i The k Encrypted information, This indicates a non-anchor node after encryption via Encryptor II. i neighboring nodes j exist t It must be sent to non-anchor nodes at all times. i The k Encrypted information; The process of decrypting the two sets of encrypted positioning information from the triangular neighbor sensors via the non-anchor node specifically includes: The non-anchor node decrypts the two sets of encrypted positioning information from the sensors in each triangular neighbor cluster according to the following formula: in, and These represent decryptor I and decryptor II, respectively. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy. This specifically includes: For each triangular neighbor set of the non-anchor point, the corresponding sensor is considered trustworthy when the two sets of angle measurement information and position estimates obtained by each sensor in the triangular neighbor set satisfy the following formula: If all sensors in the triangular neighbor set are trustworthy, the trust level of the triangular neighbor set is determined to be 1; otherwise, the trust level of the triangular neighbor set is determined to be 0.

2. The distributed secure positioning method for wireless sensor networks as described in claim 1, characterized in that, The dynamic centroid coordinates of the non-anchor node after weighted fusion of all triangular neighbor sets are determined using the following formula, based on the centroid coordinates obtained from angle measurements by sensors in the trusted triangular neighbor set: ， ； in, Let be the set of all neighbor nodes in each triangular neighbor set of non-anchor node i, and s be the set of... Any neighboring node in the middle, Let be the dynamic centroid coordinates of non-anchor node i in the weighted fusion of all triangular neighbor sets containing neighbor node s. Let be the centroid coordinates of the non-anchor node i in the triangular neighbor set r corresponding to the neighbor node s. Weight the trust scores of the triangular neighbor set r of non-anchor node i. Let be the total trust score of each triangular neighbor set of non-anchor node i. q Let be the number of triangular neighbors of non-anchor node i.

3. The distributed secure positioning method for wireless sensor networks as described in claim 2, characterized in that, The position estimate of the non-anchor node is determined by the following formula, based on the decrypted position estimate corresponding to the sensors in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set: ； in, This is the estimated position of non-anchor node i at time t+1. Let be the estimated position of non-anchor node i at time t. To update the weighting constants, is the decrypted position estimate of the neighbor node s of non-anchor node i.

4. A distributed secure positioning device for wireless sensor networks, characterized in that, include: The neighbor determination module is used to treat each sensor in the wireless sensor network that does not have its own location information as a non-anchor node, and for each non-anchor node, determine several triangular neighbor sets formed by the neighbor sensors of each non-anchor node. The encrypted transmission module is used to receive two sets of encrypted positioning information from the centralized sensors of each triangular neighbor through the non-anchor node; the two sets of encrypted positioning information are encrypted with two different keys; each set of encrypted positioning information includes angle measurement information and position estimation value. The decryption judgment module is used to decrypt the two sets of encrypted positioning information of the sensors in each triangular neighbor set through the non-anchor node. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy. The centroid coordinate determination module is used to determine the dynamic centroid coordinates of the non-anchor node after weighted fusion of the triangular neighbor sets, based on the centroid coordinates obtained from the angle measurement information of the sensors in the trusted triangular neighbor set. The positioning module is used to determine the position estimate of the non-anchor node based on the decrypted position estimate corresponding to the sensors in the trusted triangular neighbor set and the dynamic centroid coordinates of the non-anchor node after weighted fusion of the triangular neighbor sets; the two sets of encrypted positioning information are encrypted using two different keys, specifically including: The angle measurement information and position estimate are encrypted using the following formula: in, Indicates encryptor I, Indicates Encryptor II, c is a parameter in encryptor I, and c is a parameter in encryptor II. Indicates non-anchor nodes i neighboring nodes j exist t It must be sent to non-anchor nodes at all times. i The k Plaintext information, This indicates the non-anchor node after encryption by encryptor I. i neighboring nodes j exist t It must be sent to non-anchor nodes at all times. i The k Encrypted information, This indicates a non-anchor node after encryption via Encryptor II. i neighboring nodes j exist t It must be sent to non-anchor nodes at all times. i The k The encryption information; the decryption of the two sets of encrypted positioning information of the triangular neighbor sensors through the non-anchor node specifically includes: The non-anchor node decrypts the two sets of encrypted positioning information from the sensors in each triangular neighbor cluster according to the following formula: in, and These represent decryptor I and decryptor II, respectively. When the two sets of angle measurement information and position estimation values ​​obtained by each sensor in the triangular neighbor set are the same, the corresponding triangular neighbor set is determined to be trustworthy. This specifically includes: For each triangular neighbor set of the non-anchor point, the corresponding sensor is considered trustworthy when the two sets of angle measurement information and position estimates obtained by each sensor in the triangular neighbor set satisfy the following formula: If all sensors in the triangular neighbor set are trustworthy, the trust level of the triangular neighbor set is determined to be 1; otherwise, the trust level of the triangular neighbor set is determined to be 0.

5. A computer-readable storage medium, characterized in that, The storage medium stores a computer program that, when executed by a processor, implements the method as described in any one of claims 1 to 4.

6. A computer device, characterized in that, It includes a memory, a processor, and a computer program stored in the memory and executable on the processor, wherein the processor, when executing the program, implements the method as described in any one of claims 1 to 4.

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