Distributed safety positioning method, device and equipment for wireless sensor network

Abstract

The invention discloses a distributed security positioning method, device and equipment for a wireless sensor network, and relates to the technical field of wireless sensor networks. For each non-anchor node, two groups of encrypted positioning information of sensors in a triangular neighbor set are received, and the two groups of encrypted positioning information are encrypted through two groups of different keys, so that the non-anchor node can decrypt and compare; determining whether angle measurement information and position estimation values sent by sensors in each triangular neighbor set and received by the non-anchor node are safe or not, so as to establish credibility evaluation for the sensors in each triangular neighbor set, and then determining dynamic barycentric coordinates of the non-anchor node after weighted fusion of each triangular neighbor set based on a trusted triangular neighbor set; and the position estimation value of the non-anchor node is determined by combining the decrypted position estimation value corresponding to the sensor in the trusted triangular neighbor set, so that the safety and the reliability of distributed positioning of the wireless sensor network are improved.

Description

Technical Field

[0001] The present invention relates to the technical field of wireless sensor networks, and particularly relates to a distributed secure positioning method, device and equipment for wireless sensor networks. Background Art

[0002] Currently, a wireless sensor network is a network system composed of many low-power and miniature sensors. By deploying a large number of sensors, wide-area real-time monitoring and data collection can be achieved. Currently, this technology is widely used in civilian, military and industrial fields, such as target tracking, smart home, smart city, collaborative transportation and Internet of Things. In the above actual application scenarios, the lack of sensor location data will hinder collaboration and affect the efficiency and adaptability of the overall work execution. Therefore, obtaining the true location in a wireless sensor network is crucial for most applications.

[0003] In the prior art, in a wireless sensor network, there are centralized positioning methods and distributed positioning methods. The centralized positioning method usually requires a central sensor to collect all measurement information and communicate with all sensors. However, as the network scale expands, the computational complexity and communication load of the central sensor increase exponentially, resulting in a significant reduction in system reliability. In contrast, the distributed positioning method relies on each sensor itself for calculation. Non-anchor node sensors without their own location information can be located by means of distance measurement, azimuth measurement or angle measurement with the help of neighbor nodes. When some sensors are attacked or generate errors, the data of other sensors can still be used to calculate an accurate location estimate. Therefore, it has better robustness.

[0004] However, in the existing sensor networks, distributed positioning is vulnerable to network attacks due to its open distributed wireless network communication, and the possibility of suffering complex network attacks is very high, resulting in a significant reduction in the security and reliability of distributed positioning in wireless sensor networks. Summary of the Invention

[0005] Based on this, it is necessary to provide a distributed secure positioning method, device and equipment for wireless sensor networks in view of the above technical problems.

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

[0007] The present invention provides a distributed secure positioning method for wireless sensor networks, including:

[0008] Regarding each sensor without its own location information in the wireless sensor network as a non-anchor node, and for each non-anchor node, determining a number of triangular neighbor sets formed by the neighbor sensors of each non-anchor node;

[0009] Receive two groups of encrypted positioning information of sensors in each triangular neighbor set through this non-anchor node; the two groups of encrypted positioning information are encrypted by two different keys; each group of encrypted positioning information includes angle measurement information and position estimation values;

[0010] Decrypt the two groups of encrypted positioning information of sensors in each triangular neighbor set through this non-anchor node. When the two groups of angle measurement information and position estimation values decrypted by each sensor in the triangular neighbor set are the same, determine that the corresponding triangular neighbor set is trustworthy;

[0011] Determine the dynamic centroid coordinates of this non-anchor node after weighted fusion in each triangular neighbor set according to the centroid coordinates obtained from the angle measurement information of sensors in the trustworthy triangular neighbor sets;

[0012] Determine the position estimation value of this non-anchor node according to the decrypted position estimation values corresponding to sensors in the trustworthy triangular neighbor sets and the dynamic centroid coordinates of this non-anchor node after weighted fusion in each triangular neighbor set.

[0013] Optionally, the two groups of encrypted positioning information are encrypted by two different keys, specifically including:

[0014] Encrypt the angle measurement information and position estimation values through the following formula:

[0015]

[0016] Where, Represents Encryptor I, Represents Encryptor II, a is a parameter in Encryptor I, c is a parameter in Encryptor II, Represents the kth kind of plaintext information that neighbor node j of non-anchor node i at time t needs to send to non-anchor node i, Represents the kth kind of encrypted information that neighbor node j of non-anchor node i at time t needs to send to non-anchor node i after being encrypted by Encryptor I, Represents the kth kind of encrypted information that neighbor node j of non-anchor node i at time t needs to send to non-anchor node i after being encrypted by Encryptor II.

[0017] Optionally, the decryption of the two groups of encrypted positioning information of sensors in each triangular neighbor set by this non-anchor node specifically includes:

[0018] Decrypt the two groups of encrypted positioning information of sensors in each triangular neighbor set by this non-anchor node according to the following formula:

[0019]

[0020] Where, And Represent Decryptor I and Decryptor II respectively.

[0021] Optionally, when the two sets of angle measurement information and position estimation values decrypted by each sensor in the triangular neighbor set are the same, it is determined that the corresponding triangular neighbor set is trustworthy. Specifically, it includes:

[0022] For each triangular neighbor set of this non-anchor node, when the two sets of angle measurement information and position estimation values decrypted by each sensor in this triangular neighbor set satisfy the following formula, it is determined that the corresponding sensor is trustworthy:

[0023]

[0024] When each sensor in this triangular neighbor set is trustworthy, it is determined that the trust level of this triangular neighbor set is 1; otherwise, it is determined that the trust level of this triangular neighbor set is 0.

[0025] Optionally, according to the following formula, based on the centroid coordinates obtained from the angle measurement information of the sensors in the trustworthy triangular neighbor sets, the dynamic centroid coordinates of this non-anchor node after weighted fusion of each triangular neighbor set are determined:

[0026]

[0027] Where, is the set of all neighbor nodes in each triangular neighbor set of non-anchor node i, s is an arbitrary neighbor node in the set , a is (t) is the dynamic centroid coordinate of non-anchor node i after weighted fusion of each triangular neighbor set containing neighbor node s, is the centroid coordinate of non-anchor node i corresponding to neighbor node s in triangular neighbor set r, is the trust-level weighting of triangular neighbor set r, η i (t) is the total trust level of each triangular neighbor set of non-anchor node i, and q is the number of triangular neighbor sets of non-anchor node i.

[0028] Optionally, according to the following formula, based on the decrypted position estimation values corresponding to the sensors in the trustworthy triangular neighbor sets and the dynamic centroid coordinates of this non-anchor node after weighted fusion of each triangular neighbor set, the position estimation value of this non-anchor node is determined:

[0029]

[0030] Where, p i (t + 1) is the position estimation value of non-anchor node i at time t + 1, p i (t) is the position estimation value of non-anchor node i at time t, γ is the update weighting constant, p s (t) is the decrypted position estimation value corresponding to neighbor node s of non-anchor node i.

[0031] The present invention provides a distributed secure positioning device for a wireless sensor network, including:

[0032] A neighbor determination module, configured to use each sensor in the wireless sensor network without its own position information as a non-anchor node, and for each non-anchor node, determine a plurality of triangular neighbor sets formed by the neighbor sensors of each non-anchor node;

[0033] An encrypted transmission module, configured to receive two sets of encrypted positioning information of the sensors in each triangular neighbor set through the non-anchor node; the two sets of encrypted positioning information are encrypted by two different keys; each set of encrypted positioning information includes angle measurement information and a position estimate;

[0034] A decryption and determination module, configured to decrypt the two sets of encrypted positioning information of the sensors in each triangular neighbor set through the non-anchor node, and when the two sets of angle measurement information and position estimates obtained by decrypting each sensor in the triangular neighbor set are the same, determine that the corresponding triangular neighbor set is trustworthy;

[0035] A centroid coordinate determination module, configured to determine the dynamic centroid coordinate of the non-anchor node after weighted fusion of each triangular neighbor set according to the centroid coordinate obtained from the angle measurement information of the sensors in the trustworthy triangular neighbor set;

[0036] A positioning module, configured to determine the position estimate of the non-anchor node according to the decrypted position estimates corresponding to the sensors in the trustworthy triangular neighbor set and the dynamic centroid coordinate of the non-anchor node after weighted fusion of each triangular neighbor set.

[0037] The present invention provides a computer-readable storage medium, where the storage medium stores a computer program, and when the computer program is executed by a processor, the above-mentioned distributed secure positioning method for a wireless sensor network is implemented.

[0038] The present invention provides a computer device, including a memory, a processor, and a computer program stored on the memory and executable on the processor, and when the processor executes the program, the above-mentioned distributed secure positioning method for a wireless sensor network is implemented.

[0039] At least one of the above technical solutions adopted by the present invention can achieve the following beneficial effects:

[0040] In order to cope with complex network attacks in the distributed positioning of wireless sensor networks, for each non-anchor node, two groups of encrypted positioning information of sensors in its triangular neighbor set are received, and the two groups of encrypted positioning information are encrypted by two different keys, so that the non-anchor node can decrypt and compare. When the comparison is the same, it means that the data has not been tampered with and can be trusted for use in the subsequent calculation of the dynamic centroid coordinates of the non-anchor node in each triangular neighbor set. Otherwise, it means that the data has been tampered with and is not trustworthy. Then, the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set can be determined by the centroid coordinates obtained from the trustworthy triangular neighbor sets through trust-weighting, and the position estimate of the non-anchor node can be determined in combination with the decrypted position estimates corresponding to the sensors in the trustworthy triangular neighbor sets.

[0041] By using two different keys for symmetric encryption in the transmission of the positioning information between the sensors of the non-anchor node and the sensors in its triangular neighbor set, the sensors of the non-anchor node can accurately determine whether the positioning information sent by the sensors in each triangular neighbor set is secure by comparing the two decryption results, so as to establish a trustworthiness evaluation for the sensors in each triangular neighbor set and perform positioning only based on the trustworthy part, improving the security and reliability of the distributed positioning of wireless sensor networks. Brief Description of the Drawings

[0042] The drawings described herein are used to provide a further understanding of the present invention and form a part of the present invention. The illustrative embodiments of the present invention and their descriptions are used to explain the present invention and do not constitute an improper limitation of the present invention. In the drawings:

[0043] Figure 1 Schematic flow of a distributed secure positioning method for wireless sensor networks provided by the present invention Figure 1 ;

[0044] Figure 2 Schematic flow of a distributed secure positioning method for wireless sensor networks provided by the present invention Figure 2 ;

[0045] Figure 3 Schematic diagram of the measurement angle θ of sensor i provided by the present invention kij ;

[0046] Figure 4 Schematic diagram of a complex network attack provided by the present invention;

[0047] Figure 5 Schematic illustration of an encryption and decryption process provided by the present invention;

[0048] Figure 6 Schematic diagram of the privacy protection result of anti-eavesdropping provided by the present invention;

[0049] Figure 7 Schematic diagram of the detection result of a spoofing attack 1 provided by the present invention;

[0050] Figure 8 Schematic diagram of the detection result of a spoofing attack 2 provided by the present invention;

[0051] Figure 9 Schematic diagram of the position estimation and error trajectory obtained by the positioning algorithm under a complex network attack provided by the present invention;

[0052] Figure 10 Schematic diagram of a distributed security positioning device for a wireless sensor network provided by the present invention;

[0053] Figure 11 Schematic diagram of a computer device for implementing a distributed security positioning method for a wireless sensor network provided by the present invention. Detailed implementation manners

[0054] To make the objectives, technical solutions and advantages of the present invention clearer, the technical solutions of the present invention will be clearly and completely described below in conjunction with the specific embodiments of the present invention and the corresponding drawings. Obviously, the described embodiments are only a part of the embodiments of the present invention, rather than all of the embodiments. All other embodiments obtained by those of ordinary skill in the art based on the embodiments of the present invention without creative efforts shall fall within the protection scope of the present invention.

[0055] Currently, in distributed positioning technology, there are usually three methods for measurement between sensor nodes: distance measurement, azimuth measurement, and angle measurement. Compared with distance measurement, angle measurement is not significantly affected by ground unevenness and multipath effects, so it provides more reliable measurement data in complex environments; at the same time, different from azimuth measurement, angle measurement does not require the establishment of a unified coordinate system, nor does it need to handle coordinate transformation between different local coordinate systems. Therefore, angle measurement is adopted for the observations between sensors in the present invention.

[0056] The following will detail the technical solutions provided by each embodiment of the present invention in conjunction with the drawings.

[0057] Figure 1 Schematic diagram of the process of a distributed security positioning method for a wireless sensor network in the present invention Figure 1 , which specifically includes the following steps:

[0058] S101: Regarding each sensor without its own position information in the wireless sensor network as a non-anchor node, for each non-anchor node, determine a number of triangular neighbor sets formed by the neighbor sensors of each non-anchor node.

[0059] S102: Receive two groups of encrypted positioning information of sensors in each triangular neighbor set through this non-anchor node; the two groups of encrypted positioning information are encrypted with two different keys; each group of encrypted positioning information includes angle measurement information and position estimation values.

[0060] S103: Decrypt the two groups of encrypted positioning information of sensors in each triangular neighbor set through this non-anchor node. When the two groups of angle measurement information and position estimation values decrypted by each sensor in the triangular neighbor set are the same, determine that the corresponding triangular neighbor set is trustworthy.

[0061] S104: Determine the dynamic centroid coordinates of this non-anchor node after weighted fusion of each triangular neighbor set according to the centroid coordinates obtained from the angle measurement information of sensors in the trustworthy triangular neighbor sets.

[0062] S105: Determine the position estimation value of this non-anchor node according to the decrypted position estimation values corresponding to sensors in the trustworthy triangular neighbor sets and the dynamic centroid coordinates of this non-anchor node after weighted fusion of each triangular neighbor set.

[0063] For the sake of convenience of description, only the server is used as the execution entity for description below. The server mentioned in the present invention can be a server set up in a service platform, or a device such as a desktop computer or a laptop computer that can execute the solution of the present invention.

[0064] For medium and complex network attacks (such as eavesdropping, DoS attacks, spoofing attacks, etc.), the existing positioning methods cannot guarantee the privacy security and positioning accuracy of the transmitted data. The present invention proposes a two-dimensional wireless sensor network distributed security positioning method based on angles under complex network attacks, which can achieve precise positioning of the wireless sensor network under complex network attacks. For details, please refer to Figure 2 , Figure 2 which is a schematic diagram of the process of a wireless sensor network distributed security positioning method in the present invention Figure 2 .

[0065] When positioning each sensor in the wireless sensor network, based on the constructed wireless sensor network, the sensors can be divided into anchor nodes and non-anchor nodes according to whether they know their own position information.

[0066] The sensor network model is a directed graph including a point set and an edge set ε The edge starting from node i and ending at node j is represented by the ordered pair (i, j). It is represented as the combination of the edge set ε 1 and ε 2 .

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

[0068] In this embodiment, m represents meters and rad represents radians. The estimated position of each sensor is defined as p i (t) = [x i (t), y i (t)], and the true position is defined as p i = [x i , y i . The true positions of the sensors are set as, p 1 = [-2.5m, -2m], p 2 = [2.5m, -2m], p 3 = [0m, 3m], p 4 = [-1.5m, -1m], p 5 = [-0.25m, 0.5m], p 6 = [0m, -0.5m], p 7 = [1.5m, -1m], p 8 = [0.25m, 0.5m], p 9 = [0m, 0m], p 10 = [0m, 2m].

[0069] The initial position estimates of the non-anchor nodes are randomly set as p 4 (0) = [-1m, -3m], p 5 (0) = [-0.25m, -0.5m], p 6 (0) = [2m, 3m], p 7 (0) = [3m, 0m], p 8 (0) = [-2m, -2m], p 9 (0) = [-2m, 1m].

[0070] The neighbor sets of non-anchor node 4 are {1, 5, 6}, the neighbor sets of non-anchor node 5 are {4, 8, 10}, {4, 9, 10}, {4, 6, 10}, the neighbor sets of non-anchor node 6 are {4, 7, 9}, {4, 5, 7}, {4, 7, 8}, non-anchor node 7 is {2, 6, 8}, non-anchor node 8 is {5, 7, 10}, {6, 7, 10}, {9, 7, 10}, non-anchor node 9 is {5, 6, 8}, and node 10 is {3, 5, 8}. Define the error between the true position and the estimated position of non-anchor node i 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 outside the GPS-denied area as anchor nodes. The convex hull formed by all anchor nodes covers the entire GPS-denied area, so that the positioning algorithm described in this invention can be used to locate all sensors (non-anchor nodes) within the GPS-denied area.

[0072] Then, lidar and depth cameras can be used to measure distances and angles, and the triangular neighbor sets of sensor nodes can be determined. For example, sensor non-anchor node i uses lidar and depth cameras to measure the angle between two adjacent sensor nodes j and k, denoted as θ jik , satisfying θ jik ≤ π, as shown in Figure 3 . Figure 3 This is a schematic diagram of a sensor i measuring the angle θ kij in this invention. Figure 3 shows the schematic of sensor non-anchor node i measuring the angle between two adjacent sensor nodes j and k within a limited range.

[0073] For each non-anchor node i, finding the triangular neighbor set Δ i is an important step in the positioning algorithm. Given the deployment density, non-anchor node i can set an initial communication radius r i to determine its neighbor set Υ(i, r i ) = {j ∈ Φ: d ij < r i}, and then select any three neighbor nodes in Υ(i, r i ) and test whether they are located inside the convex hull of these three neighbor nodes. If all tests fail, non-anchor node i adaptively increases its communication radius by a small increment. By repeating this process, the triangular neighbor set Δ i can be finally determined. After determining the triangular neighbor set, each non-anchor node i will receive Δ iThe information sent by the middle sensor node (including angle measurement information and positioning estimation value). The data packets sent by the neighbors (assumed to be j, k, l) of the non-anchor node i at time t are expressed as:

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

[0075] Suppose there are four nodes i, j, k, l in a two-dimensional space, and their positions are respectively expressed as There is a node i position representation: p i = a ij p j + a ik p k + a il p l , where a i. Represents the barycentric coordinates, and the barycentric coordinates can be calculated by the following formula:

[0076] According to the Cayley-Menger determinant, it can be deduced that:

[0077]

[0078] Furthermore, the calculation formula for the barycentric coordinates is obtained:

[0079]

[0080] Considering that the triangular neighbor set of the non-anchor node i may not be unique, in the ideal scenario without network attacks, assume that the non-anchor node i has q triangular neighbor sets, that is Then the set of all nodes in the triangular neighbor set of node i is expressed as In order to make the barycentric coordinate representation more accurate, it is necessary to perform average weighted fusion on the barycentric coordinates under different triangular neighbor sets, that is:

[0081] Furthermore, precise positioning can be achieved through distributed iteration, and the position estimation update mechanism for node i is:

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

[0083] Among them,

[0084] When sensor i considers both the current position update result and the historical moment information in iterative positioning, the iterative form is described as:

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

[0086] Then the matrix - form position update expression of the entire sensor network becomes: where D=(1 - γ)I n-3 +γC.

[0087] To cope with complex network attacks, the present invention proposes a distributed security positioning method. The said complex network attacks are divided into three cases, as Figure 4 shown, Figure 4 which is a schematic diagram of a complex network attack in the present invention:

[0088] 1) First, the attacker inserts into the communication link, captures the data being sent and forwards the original data, which will lead to privacy leakage. The present invention copes with this by designing a symmetric - encryption privacy - protection scheme, as Figure 4 shown in part (a).

[0089] 2) Second, the attacker inserts into the communication link, captures the data being sent and does not forward the data, resulting in the blocked transmission of data and the sensor nodes being unable to receive any information. When a sensor node i cannot receive the information of neighbor node j at time t, it is considered that the communication link from node j to node i is under attack. Therefore, there is no need to specifically design a detection strategy for this type of attack, as Figure 4 shown in part (b).

[0090] 3) Third, the attacker inserts into the communication link, captures the data being sent and tampers with the data, resulting in the estimated position of the sensor converging to an incorrect position. The present invention determines whether it is under attack by comparing the results obtained from double - key encryption and decryption, as Figure 4 shown in part (c).

[0091] For the information sender, it encrypts the plain - text data packet to be sent. Symmetric encryption is a simple and effective data - encryption method, which can effectively prevent unauthorized eavesdropping and data tampering. Symmetric encryption uses a single key for data encryption and decryption, greatly simplifying the process of key management. Its calculation process is not only simple, but also has low energy consumption and small computational - resource requirements, and is especially 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, the attacker can eavesdrop on the data packet The angle information and position information therein. The present invention designs a symmetric encryption privacy protection scheme. Symmetric encryption uses one key for encryption and decryption of two data. At the same time, the sender uses symmetric encryption to independently encrypt the same plaintext twice to generate two ciphertexts; the receiver decrypts the two ciphertexts respectively, and judges whether the data is tampered with during the transmission process by comparing whether the decryption results are the same. Figure 5 It is a schematic diagram for explaining the encryption and decryption process in the present invention. Figure 5 Part (a) is the encryption schematic, and part (b) is the decryption schematic. The transmitted information is as follows:

[0093] Among them, and represent the encrypted information sent by neighbor node j to sensor node i at time t. Denote the plaintext θ ijk , θ ijl , θ kjl , x j (t), y j (t) as ciphertext denote as ciphertext denote as

[0094] Key generation: Before sending information, select a, c ∈ (1, ∞) as the keys I and II for all sensors, and this key is not transmitted during the data transmission process.

[0095] plaintext is encrypted into ciphertext The angle measurement information and position estimation value can be encrypted by the following formula:

[0096]

[0097] Among them, represents the encryptor I, represents the encryptor II, a is the parameter in the encryptor I, c is the parameter in the encryptor II, represents the k-th kind of plaintext information that neighbor node j of non-anchor node i wants to send to non-anchor node i at time t, represents the k-th kind of encrypted information that neighbor node j of non-anchor node i wants to send to non-anchor node i at time t after being encrypted by the encryptor I, represents the k-th kind of encrypted information that neighbor node j of non-anchor node i wants to send to non-anchor node i at time t after being encrypted by the encryptor II.

[0098] Figure 6 It is a schematic diagram of the privacy protection result against eavesdropping in the present invention. Figure 6Part (a) shows a schematic of Encryption Scheme 1, and part (b) shows a schematic of Encryption Scheme 2. Both parts compare and analyze the ciphertext obtained by the attacker through eavesdropping with the original text before encryption by the sensor node. The abscissa represents time or the number of iteration steps, and the ordinate 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 estimation value of each triangular neighbor set according to the following formula:

[0100]

[0101] Where and represent Decryptor I and Decryptor II respectively.

[0102] The present invention determines whether the data has been tampered with during transmission by comparing whether the outputs of the two decryptions are the same. Here, for each triangular neighbor set of the non-anchor point, when the two sets of angle measurement information and position estimation values decrypted by the sensors in the triangular neighbor set satisfy the following formula, it is determined that the data of the corresponding sensor has not been tampered with and is trustworthy; otherwise, it is considered to have been tampered with:

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

[0104] Figure 7 is a schematic diagram of the detection result of a spoofing attack 1 in the present invention. Figure 7 The simulated attack type in it is directly tampering with the transmitted information. The abscissa represents time or the number of iteration steps of the sensor position, and the ordinate represents the attack state. 0 indicates no attack, and 1 indicates an attack. Figure 7 The time distribution of the detected attacked moments is compared with the time distribution of the actual attacks launched by the attacker to demonstrate the effectiveness of the present invention.

[0105] Figure 8 is a schematic diagram of the detection result of a spoofing attack 2 in the present invention. Figure 7 The simulated attack type in it is sending the intercepted transmitted information. The abscissa represents time or the number of iteration steps of the sensor position, and the ordinate represents the attack state. 0 indicates no attack, and 1 indicates an attack. Figure 8 The time distribution of the detected attacked moments is compared with the time distribution of the actual attacks launched by the attacker to demonstrate the effectiveness of the present invention.

[0106] Subsequently, the barycentric coordinates can be fused and weighted based on the trustworthiness evaluation mechanism, which is a quantitative tool used to evaluate the credibility of communication, data, and participants in fields such as network security, social networks, and sensor networks. It collects and analyzes various metrics to determine the degree of trust that a system or user can rely on in the face of uncertainty and potential risks, thereby helping to make more informed decisions.

[0107] All triangular neighbor sets of the non-anchor node i of the sensor 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 attacked by a complex network; Γ i (t) represents the triangular neighbor set that has been attacked by a complex network. The total trustworthiness of each triangular neighbor set of the non-anchor node i is denoted as:

[0108] where is the sub-trustworthiness corresponding to the triangular neighbor set of the non-anchor node i when and when If the trustworthiness η i (t) = 0, it indicates 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] The dynamic barycentric coordinate of the non-anchor node i of the sensor relative to a triangular neighbor set is:

[0110] The weighted dynamic barycentric coordinate of the sensor i relative to all triangular neighbor sets , or the dynamic barycentric coordinate of the non-anchor node i after weighted fusion of each triangular neighbor set containing the neighbor node s, is:

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

[0112] where p i (t + 1) is the position estimate value of the non-anchor node i at time t + 1, p i (t) is the position estimate value of the non-anchor node i at time t, γ is the update weighting constant, and p s (t) is the decrypted position estimate value corresponding to the neighbor node s of the non-anchor node i.

[0113] When the credibility η i (t) of sensor i > 0, even if there are risks in the communication environment, its position estimate can still be inferred at the next moment t+1. However, if the credibility η i (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 credibility at a subsequent moment is greater than zero, at which time the position estimate will be updated.

[0114] Figure 9 It is a schematic diagram of the position estimate and error trajectory obtained by the positioning algorithm under a complex network attack in the present invention. Figure 9 In part (a), it is a schematic diagram of the position estimate trajectory, where the abscissa corresponds to the position coordinate x-axis and the ordinate corresponds to the position coordinate y-axis; in part (b), it is a schematic diagram of the positioning error trajectory, where the abscissa represents time or the number of iteration steps, the ordinate represents different non-anchor nodes of sensors, and the vertical coordinate represents the positioning error value. It can be seen that even under a complex network attack, as the number of iteration steps increases, the positioning errors of each non-anchor node of sensors converge to an effective range.

[0115] Based on Figure 1 the wireless sensor network distributed security positioning method shown, in order to cope with complex network attacks in the distributed positioning of the wireless sensor network in the present invention, for each non-anchor node, two groups of encrypted positioning information of sensors in its triangular neighbor set are received, and the two groups of encrypted positioning information are encrypted by two different keys, so that the non-anchor node can decrypt and compare. When the comparison is the same, it means that the data has not been tampered with and can be trusted for application in the calculation of the dynamic centroid coordinates of the non-anchor node in each triangular neighbor set. Otherwise, it means that the data has been tampered with and is not trustworthy. Then, the dynamic centroid coordinates of the non-anchor node after weighted fusion of each triangular neighbor set can be determined by the centroid coordinates obtained from the trustworthy triangular neighbor sets through trust weighting, and combined with the decrypted position estimate values corresponding to the sensors in the trustworthy triangular neighbor sets, the position estimate value of the non-anchor node can be determined.

[0116] In the present invention, by using two different keys for symmetric encryption in the transmission of the positioning information between the sensors of the non-anchor node and the sensors in its triangular neighbor set, the sensors of the non-anchor node can accurately determine whether the positioning information sent by the sensors in each triangular neighbor set received by the non-anchor node is secure by comparing the two decryption results, so as to establish a trustworthiness evaluation for the sensors in each triangular neighbor set and perform positioning only based on the trustworthy part, improving the security and reliability of the distributed positioning of the wireless sensor network.

[0117] The sensor network positioning method proposed by the present invention is only angle-distributed, and only a small amount of online calculation is required to achieve the positioning of the entire sensor network, avoiding the risk of energy consumption. In addition, since the angle-distributed positioning can make full use of the historical position information of neighbor nodes, only a small number of anchor points are required, and it has better robustness compared with the centralized positioning method, making it suitable for complex positioning environments.

[0118] The key used in the present invention is not transmitted, preventing privacy leakage; the present invention uses symmetric encryption, enabling us to predict whether the data has been tampered with. Symmetric encryption greatly simplifies the process of key management. Its calculation process is not only simple but also has low energy consumption and minimal computing resource requirements, making it particularly suitable for sensor devices powered by batteries and with limited resources.

[0119] The present invention uses a trust evaluation strategy to achieve precise positioning of non-anchor nodes. The trust evaluation mechanism is a quantitative tool used to evaluate the trust of communication, data, and participants in fields such as network security, social networks, and sensor networks. It collects and analyzes various metrics to determine the degree of trust that a system or user can rely on when facing uncertainties and potential risks, thereby assisting in making more informed decisions.

[0120] When applying the distributed secure positioning method for wireless sensor networks provided by the present invention, it is not necessary to execute according to Figure 1 the order of the steps shown. The specific execution order of each step can be determined as needed, and the present invention does not limit this.

[0121] The above is the 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, as Figure 10 shown.

[0122] Figure 10 is a schematic diagram of a distributed secure positioning device for wireless sensor networks provided by the present invention, including:

[0123] A neighbor determination module 201, configured to use each sensor in the wireless sensor network that does not have its own position information as a non-anchor node, and for each non-anchor node, determine a number of triangular neighbor sets formed by the neighbor sensors of each non-anchor node;

[0124] An encrypted transmission module 202, configured to receive two sets of encrypted positioning information of the sensors in each triangular neighbor set through this 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 a position estimate;

[0125] The decryption judgment module 203 is configured 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 decrypted by the sensors in the triangular neighbor set are the same, it is determined that the corresponding triangular neighbor set is trustworthy;

[0126] The centroid coordinate determination module 204 is configured to determine the dynamic centroid coordinate of the non-anchor node after weighted fusion in each triangular neighbor set according to the centroid coordinate obtained from the angle measurement information of the sensors in the trustworthy triangular neighbor set;

[0127] The positioning module 205 is configured to determine the position estimation value of the non-anchor node according to the decrypted position estimation values corresponding to the sensors in the trustworthy triangular neighbor set and the dynamic centroid coordinate of the non-anchor node after weighted fusion in each triangular neighbor set.

[0128] For the specific limitations of the wireless sensor network distributed security positioning device, reference can be made to the limitations of the wireless sensor network distributed security positioning method in the above text, which will not be elaborated here. Each module in the above wireless sensor network distributed security positioning device can be implemented in whole or in part by software, hardware, and their combination. The above modules can be embedded in the processor in the computer device in hardware form or be independent of it, or can be stored in the memory in the computer device in software form, so that the processor can call and execute the operations corresponding to the above modules.

[0129] The present invention also provides a computer-readable storage medium, which stores a computer program, and the computer program can be used to execute the above Figure 1 provided wireless sensor network distributed security positioning method.

[0130] The present invention also provides Figure 11 the structural schematic diagram of the computer device shown in Figure 11 As shown, at the hardware level, the computer device includes a processor, an internal bus, a network interface, a memory, and a non-volatile memory. Of course, it may also include other hardware required for other services. The processor reads the corresponding computer program from the non-volatile memory into the memory and then runs it to implement the above Figure 1 provided wireless sensor network distributed security positioning method.

[0131] Those of ordinary skill in the art can understand that all or part of the processes in the methods of the above embodiments can be completed by instructing relevant hardware through a computer program. The computer program can be stored in a non-volatile computer-readable storage medium. When the computer program is executed, it can include the processes of the embodiments of the above methods. Among them, any reference to a memory, storage, database, or other medium used in the embodiments provided by the present invention can include at least one of non-volatile and volatile memories. Non-volatile memory can include read-only memory (ROM), magnetic tape, floppy disk, flash memory, or optical memory, 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 arbitrarily. For the sake of concise description, 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, it should be considered as within the scope recorded by the present invention.

Claims

1. A distributed secure positioning method for a wireless sensor network, characterized in that: include: Each sensor in the wireless sensor network that does not have its own location information is regarded as a non-anchor node, and for each non-anchor node, a number of triangular neighbor sets formed by neighbor sensors of each non-anchor node are determined; The non-anchor node receives two sets of encrypted positioning information from sensors in each triangular neighbor set; the two sets of encrypted positioning information are encrypted using two different sets of keys; each set of encrypted positioning information includes angle measurement information and position estimation value; Decrypting two sets of encrypted positioning information of sensors in each triangular neighbor set through the non-anchor node, and when the two sets of angle measurement information and position estimation values ​​decrypted by each sensor in the triangular neighbor set are the same, determining that the corresponding triangular neighbor set is trustworthy; Determine the dynamic center of gravity coordinates of the non-anchor node after weighted fusion of each triangular neighbor set according to the center of gravity coordinates obtained from the angle measurement information of the sensors in the trusted triangular neighbor set; The position estimation value of the non-anchor node is determined according to the decrypted position estimation value corresponding to the sensor in the trusted triangular neighbor set and the dynamic center of gravity coordinates of the non-anchor node after weighted fusion in each triangular neighbor set.

2. The distributed secure positioning method for wireless sensor networks according to claim 1, characterized in that: The two sets of encrypted positioning information are encrypted by two sets of different keys, specifically including: The angle measurement information and position estimate are encrypted as follows: in, represents the encryptor I, represents encryptor II, a is the parameter in encryptor I, c is the parameter in encryptor II, It indicates the kth plaintext information that neighbor node j of non-anchor node i wants to send to non-anchor node i at time t. represents the kth encrypted information that the neighbor node j of non-anchor node i wants to send to non-anchor node i at time t after being encrypted by encryptor I, It indicates the kth encrypted information that the neighbor node j of non-anchor node i is to send to non-anchor node i at time t after being encrypted by encryptor II.

3. The wireless sensor network distributed security positioning method according to claim 2, characterized in that: Decrypting two sets of encrypted positioning information of sensors in each triangle neighbor set through the non-anchor node specifically includes: The two sets of encrypted positioning information of sensors in each triangle neighbor set are decrypted by the non-anchor node according to the following formula: in, and They represent decryptor I and decryptor II respectively.

4. The wireless sensor network distributed secure positioning method according to claim 3, characterized in that: When the two sets of angle measurement information and position estimation values ​​decrypted by the sensors in the triangular neighbor set are the same, determining that the corresponding triangular neighbor set is trustworthy specifically includes: For each triangular neighbor set of the non-anchor point, when the two sets of angle measurement information and position estimation values ​​decrypted by each sensor in the triangular neighbor set satisfy the following formula, the corresponding sensor is determined to be trustworthy: When all sensors in the triangular neighbor set are trustworthy, the trust degree of the triangular neighbor set is determined to be 1; otherwise, the trust degree of the triangular neighbor set is determined to be 0.

5. The distributed secure positioning method for wireless sensor networks according to claim 1, characterized in that: The dynamic center of gravity coordinates of the non-anchor node after weighted fusion of each triangular neighbor set are determined by the following formula based on the center of gravity coordinates obtained from the angle measurement information of the sensors in the trusted triangular neighbor set: in, is the set of all neighbor nodes in each triangle neighbor set of non-anchor node i, and s is the set Any neighbor node in a is (t) is the dynamic centroid coordinate of non-anchor node i after weighted fusion of each triangular neighbor set containing neighbor node s, is the centroid coordinate of the neighbor node s corresponding to the non-anchor node i in the triangular neighbor set r, is the trust weight of the triangular neighbor set r of non-anchor node i, η i (t) is the total trust of each triangular neighbor set of non-anchor node i, and q is the number of triangular neighbor sets of non-anchor node i.

6. The distributed secure positioning method for wireless sensor networks according to claim 5, 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 sensor in the trusted triangular neighbor set and the dynamic center of gravity coordinates of the non-anchor node after weighted fusion in each triangular neighbor set: Among them, p i (t+1) is the estimated position of non-anchor node i at time t+1, p i (t) is the estimated position of non-anchor node i at time t, γ is the update weight constant, p s (t) is the decrypted position estimate corresponding to the neighbor node s of the non-anchor node i.

7. A wireless sensor network distributed security positioning device, characterized in that: include: A 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 a number of triangular neighbor sets formed by neighbor sensors of each non-anchor node; An encrypted transmission module is used to receive two sets of encrypted positioning information of sensors in each triangle neighbor set through the non-anchor node; the two sets of encrypted positioning information are encrypted by two sets of different keys; each set of encrypted positioning information includes angle measurement information and position estimation value; A decryption judgment module is used to decrypt two sets of encrypted positioning information of sensors in each triangular neighbor set through the non-anchor node, and when the two sets of angle measurement information and position estimation values ​​decrypted by each sensor in the triangular neighbor set are the same, it is determined that the corresponding triangular neighbor set is trustworthy; A barycentric coordinate determination module, used to determine the dynamic barycentric coordinates of the non-anchor node after weighted fusion of each triangular neighbor set based on the barycentric 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 according to the decrypted position estimate corresponding to the sensor in the trusted triangular neighbor set and the dynamic center of gravity coordinates of the non-anchor node after weighted fusion in each triangular neighbor set.

8. A computer-readable storage medium, characterized in that: The storage medium stores a computer program, and when the computer program is executed by a processor, the method according to any one of claims 1 to 6 is implemented.

9. A computer device, characterized in that: The method comprises a memory, a processor and a computer program stored in the memory and executable on the processor, wherein when the processor executes the program, the method according to any one of claims 1 to 6 is implemented.

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