CN110944383B - A security localization method for wireless sensor network against cloning attack - Google Patents

Abstract

The invention relates to a wireless sensor network safety positioning method aiming at clone attack, which considers the defects of large energy consumption, poor detection resistance and the like of clone nodes from the angle of an attacker, detects the clone nodes in a wireless sensor network by a mean square error consistency method based on the safety positioning process of RSSI ranging, eliminates the clone nodes in the wireless sensor network by adopting a minimum mean square error method, finally positions unknown nodes in a safe environment, performs positioning calculation again by the unknown nodes through the rest beacon nodes, and obtains a positioning result by a positioning method based on RSSI ranging. The method can well remove the clone node, reduce the influence of the clone node on the positioning of the unknown node, and improve the positioning precision of the unknown node.

Description

A security localization method for wireless sensor network against cloning attack

technical field

The invention belongs to the technical field of the Internet of Things, relates to wireless sensor network technology, and in particular relates to a wireless sensor network security positioning method for cloning attacks.

Background technique

The process of ranging and positioning based on Received Signal Strength Indicator (English: Received Signal Strength Indicator, RSSI for short) mainly has two stages. In the first stage, the distance from the unknown node to the beacon node is calculated. Beacon nodes periodically send information such as ID and location coordinates to surrounding nodes, and unknown nodes receive information through wireless signals. In free space, the node transmits wireless signals, and the theoretical model is usually the attenuation model RSSI(d)=RSSI(d ₀ )-10αlog(d/d ₀ )+P _n , where RSSI indicates that the unknown node receives the beacon The signal strength value of the node, d represents the distance between the unknown node and the beacon node, d ₀ is the reference distance, α represents the path loss index, and P _n represents a Gaussian random variable with a mean value of 0. The attenuation model is a classical calculation method to measure the distance from unknown nodes to beacon nodes. α and P _n need to be set according to the specific environment. When the signal strength value sent by the unknown node to the beacon node is known, the distance between the two can be calculated. In the second stage, the location of the unknown node is calculated. In the first stage, the distance from the beacon node to the unknown node is calculated, and then combined with the position coordinates of the beacon node, the unknown node uses the maximum likelihood estimation method to obtain its own position information.

Beacon nodes deployed in wireless sensor networks can provide location services to unknown nodes. The interference of noise and obstacles during the RSSI ranging process will affect the calculation of the distance from the unknown node to the beacon node, resulting in a deviation between the estimated positioning position of the unknown node and the real position. Wireless sensor networks are usually deployed in unguarded hostile environments and are vulnerable to cloning attacks. Cloning attacks capture nodes in the network, extract information such as the key, location, and identity of the node, and create cloned nodes from this information. When there are cloned nodes in the network, the estimated position of the unknown node is seriously deviated from the real position. Since clone nodes are deployed in different locations in the network, the location of unknown nodes is misled and the location accuracy is seriously affected.

SUMMARY OF THE INVENTION

Aiming at the above-mentioned shortcomings of the prior art such as low positioning accuracy, the present invention provides a wireless sensor network security positioning method for cloning attacks, which can effectively eliminate clone nodes and improve the positioning accuracy of unknown nodes.

In order to achieve the above object, the present invention provides a wireless sensor network security positioning method for cloning attacks, which includes the following steps:

(1) The beacon node periodically sends its own ID and location coordinates to its surrounding nodes. When the known unknown node receives the signal strength value sent by the beacon node, the attenuation model of the signal strength value is used to calculate the distance between the beacon node and the unknown node. The distance of the node; through the calculated distance from the beacon node to the unknown node, combined with the position coordinates of the beacon node, the estimated position of the unknown node is obtained.

(2) Use the mean square error consistency to detect whether there is a clone attack in the wireless sensor network according to the mean square error of the estimated position of the unknown node. If there is no clone attack, the estimated position of the unknown node obtained in step (1) is unknown. The safe positioning position of the node; if there is a cloning attack, remove the cloned node until the minimum mean square error of the unknown node is less than the set mean square error threshold γ, repeat the steps of step (1), and the estimated position of the unknown node obtained is unknown. The safe location of the node.

Preferably, the wireless sensor network includes m, m≥3 beacon nodes, multiple unknown nodes and n,0≤n<m clone nodes, each beacon node has a unique ID, and each beacon node has a unique ID. The node knows its own position coordinates, the communication radius of the beacon node, the unknown node and the clone node is R, and there is no communication data loss between the nodes.

Preferably, the attenuation model of the signal strength value is expressed as: RSSI(d)=RSSI(d ₀ )-10αlog(d/d ₀ )+P _n , where RSSI represents the signal strength value of the unknown node receiving the beacon node, d represents the distance between the unknown node and the beacon node, d ₀ is the reference distance, α represents the path loss index, and P _n represents a Gaussian random variable with a mean value of 0; in the wireless sensor network, the position coordinates of m beacon nodes are respectively ( x ₁ ,y ₁ ),(x ₂ ,y ₂ ),...,(x _m ,y _m ), the distances from the unknown node to the beacon node are respectively d ₁ ,d ₂ ,...,d _m , Assuming that the position coordinates of the unknown node are (x, y), the formula for calculating the position coordinates of the unknown node is expressed as:

From the first equation of formula (1) to the m-1th equation, subtract the mth equation in turn to obtain a linear equation, where:

In the formula, A and b represent the coefficient matrix, and X represents the actual position coordinates of the unknown node;

其中，

表示未知节点的估计位置坐标。Using the maximum likelihood estimation method, the estimated position coordinates of the unknown nodes are calculated as:

in,

Represents the estimated location coordinates of the unknown node.

Preferably, in step (2), a specific method for detecting whether there is a clone attack in the wireless sensor network according to the mean square error of the estimated position of the unknown node by using the mean square error consistency:

The position coordinates of the estimated position obtained by the unknown node are relatively concentrated on the two-dimensional plane, which is represented as a dense area centered on the real position of the unknown node, and the mean square error of the unknown node is consistent. If there are clones in the wireless sensor network node, the calculated mean square error value of the unknown node is inconsistent, and is greater than the mean square error value of the unknown node in the safe state; the mean square error of the unknown node is calculated by formula (5), and formula (5) is expressed as:

表示未知节点的均方误差，x_j表示第j个信标节点的位置坐标的横坐标，y_j表示第j个信标节点的位置坐标的纵坐标，

表示未知节点的位置坐标的横坐标，

表示未知节点的位置坐标的纵坐标。In the formula,

represents the mean square error of the unknown node, x _j represents the abscissa of the position coordinate of the jth beacon node, y _j represents the ordinate of the position coordinate of the jth beacon node,

the abscissa representing the location coordinates of the unknown node,

The ordinate representing the location coordinates of the unknown node.

Preferably, in step (2), the method for eliminating the clone node is:

(1) Assuming that there are p, p=m+n nodes in the communication range of the unknown node, select p-1 nodes from the p nodes as a group for calculating the position of the unknown node, and for each group obtained The position of the unknown node is calculated and the mean square error of the position of the unknown node is calculated. There are p mean square errors in total, which are recorded as

将M与γ做比较，若M<γ，则无线传感器网络中没有克隆节点；若M>γ，则无线传感器网络中有克隆节点，从均方误差最小的一组节点中随机剔除一个节点；(2) Select the smallest set of mean square errors in Y, denoted as

Compare M with γ, if M<γ, there is no clone node in the wireless sensor network; if M>γ, there is a clone node in the wireless sensor network, and a node is randomly selected from a group of nodes with the smallest mean square error;

(3) Select p-2 nodes from the p-1 nodes as a group for calculating the position of the unknown node, and continue to perform the above steps (1) and (2) until the minimum set of mean square errors M If it is less than γ, stop the algorithm and complete the elimination of clone nodes.

Compared with the prior art, the beneficial effects of the present invention are:

From the attacker's point of view, the present invention considers the situation that unknown nodes, beacon nodes and clone nodes are randomly deployed in the wireless sensor network. In the process of secure localization based on RSSI ranging, the clone nodes in the wireless sensor network are detected by the method of mean square error consistency, and the clone nodes in the wireless sensor network are eliminated by the method of minimum mean square error, and finally the unknown nodes are located. In a safe environment, the unknown node re-calculates the positioning through the remaining beacon nodes, and obtains the positioning result through the positioning method based on RSSI ranging. The invention can eliminate clone nodes well, reduce the influence of clone nodes on the positioning of unknown nodes, and improve the positioning accuracy of unknown nodes.

Description of drawings

Fig. 1 is a schematic diagram of the influence of cloning attack on the location of unknown nodes in the existing wireless sensor network;

2 is a schematic diagram of the location of a clone node participating in an unknown node in a wireless sensor network security location method for cloning attacks according to an embodiment of the present invention;

3 is a schematic diagram illustrating the comparison of the influence of the number of cloned nodes on the mean square error of the estimated position of unknown nodes in the wireless sensor network security positioning method for cloning attacks according to an embodiment of the present invention;

4 is a schematic diagram illustrating the comparison of the influence of the number of clone nodes on the location of unknown nodes in the wireless sensor network security location method for cloning attacks according to an embodiment of the present invention;

5 is a schematic diagram illustrating the comparison of the influence of the distance from the cloned beacon node to the unknown node on the mean square error of the estimated position of the unknown node in the wireless sensor network security positioning method for cloning attacks according to an embodiment of the present invention;

6 is a schematic diagram illustrating the comparison of the influence of the distance from the cloned beacon node to the unknown node on the positioning of the unknown node in the wireless sensor network security positioning method for cloning attacks according to an embodiment of the present invention;

FIG. 7 is a performance comparison diagram of the wireless sensor network security positioning method for cloning attack according to the present invention and different existing positioning methods.

Detailed ways

Hereinafter, the present invention will be specifically described through exemplary embodiments. It should be understood, however, that elements, structures and features of one embodiment may be beneficially combined in other embodiments without further recitation.

The interference of noise and obstacles during the RSSI ranging process will affect the calculation of the distance from the unknown node to the beacon node, resulting in a deviation between the estimated positioning position of the unknown node and the real position. Referring to Figure 1, when there are clone nodes in the wireless sensor network, the estimated position of the unknown node is seriously deviated from the real position. In Figure 1, the triangle represents the beacon node, the square represents the clone node, and the circle represents the unknown node.

The mean square error can well reflect the degree of deviation between the estimator and the estimated value. When there are only beacon nodes in the wireless sensor network, the mean square error of unknown nodes fluctuates within a certain range. When there are clone nodes in the wireless sensor network, the mean square error of the estimated position of the unknown node increases with the increase of the number of clone nodes. According to whether there are cloned nodes, the mean square error value of unknown nodes is inconsistent. The invention provides a wireless sensor network security positioning method for cloning attacks. Based on the security positioning process of RSSI ranging, the method of mean square error consistency is used to detect the clone nodes, and the clone nodes are eliminated to ensure that the unknown nodes are in a safe environment. Positioning with high positioning accuracy.

Specifically, the wireless sensor network includes m, m≥3 beacon nodes, multiple unknown nodes and n,0≤n<m clone nodes, each beacon node has a unique ID, and each beacon node has Knowing its own position coordinates, the communication radius of beacon nodes, unknown nodes and clone nodes are all R, and no communication data is lost between nodes. The clone node participates in the positioning process of the unknown node by obtaining the ID and unknown coordinate information of the beacon node, which can affect the positioning accuracy of the unknown node. The performance and functions of the nodes are the same, and they have the function of data fusion.

The above-mentioned wireless sensor network security positioning method for cloning attack provided by the present invention specifically includes the following steps:

(1) The beacon node periodically sends its own ID and location coordinates to its surrounding nodes. When the known unknown node receives the signal strength value sent by the beacon node, the attenuation model of the signal strength value is used to calculate the distance between the beacon node and the unknown node. The distance of the node; through the calculated distance from the beacon node to the unknown node, combined with the position coordinates of the beacon node, the estimated position of the unknown node is obtained.

Specifically, the attenuation model of the signal strength value is expressed as: RSSI(d)=RSSI(d ₀ )-10αlog(d/d ₀ )+P _n , where RSSI represents the signal strength value of the unknown node receiving the beacon node, d represents the distance between the unknown node and the beacon node, d ₀ is the reference distance, α represents the path loss index, and P _n represents a Gaussian random variable with a mean value of 0. Among them, α and P _n need to be set according to specific environmental assumptions. In free space, the nodes transmit wireless signals. When the known unknown node receives the signal strength value sent by the beacon node, it can be used to calculate the distance between the two.

Specifically, in the wireless sensor network, the position coordinates of m beacon nodes are respectively (x ₁ , y ₁ ), (x ₂ , y ₂ ),..., (x _m , y _m ), and the unknown nodes are The distances to the beacon nodes are respectively d ₁ , d ₂ ,...,d _m . Assuming that the position coordinates of the unknown nodes are (x, y), the formula for calculating the position coordinates of the unknown nodes is expressed as:

From the first equation of formula (1) to the m-1th equation, subtract the mth equation in turn to obtain a linear equation, where:

In the formula, A and b represent the coefficient matrix, and X represents the actual position coordinates of the unknown node;

其中，

表示未知节点的估计位置坐标。此处，计算未知节点的估计位置坐标时，还可以采用最小二乘法。Using the maximum likelihood estimation method, the estimated position coordinates of the unknown nodes are calculated as:

in,

Represents the estimated location coordinates of the unknown node. Here, when calculating the estimated position coordinates of the unknown node, the least squares method can also be used.

(2) Use the mean square error consistency to detect whether there is a clone attack in the wireless sensor network according to the mean square error of the estimated position of the unknown node. If there is no clone attack, the unknown node is located in a safe environment. Step (1) obtains The estimated position of the unknown node is the safe positioning position of the unknown node; if there is a cloning attack, the cloned node is eliminated until the minimum mean square error of the unknown node is less than the set mean square error threshold γ, then it is determined that the unknown node is located in a safe environment. , repeating the steps of step (1), the obtained estimated position of the unknown node is the safe positioning position of the unknown node. It should be noted that the mean square error threshold γ is the upper limit of error calculated through experiments in a safe state.

Specifically, using the mean square error consistency to detect whether there is a clone attack in the wireless sensor network according to the mean square error of the estimated position of the unknown node is as follows:

The position coordinates of the estimated position obtained by the unknown node are relatively concentrated on the two-dimensional plane, which is represented as a dense area centered on the real position of the unknown node, and the mean square error of the unknown node is consistent. If there are clones in the wireless sensor network node, the calculated mean square error value of the unknown node is inconsistent, and is greater than the mean square error value of the unknown node in the safe state; the mean square error of the unknown node is calculated by formula (5), and formula (5) is expressed as:

表示未知节点的均方误差，x_j表示第j个信标节点的位置坐标的横坐标，y_j表示第j个信标节点的位置坐标的纵坐标，

表示未知节点的位置坐标的横坐标，

表示未知节点的位置坐标的纵坐标。In the formula,

represents the mean square error of the unknown node, x _j represents the abscissa of the position coordinate of the jth beacon node, y _j represents the ordinate of the position coordinate of the jth beacon node,

the abscissa representing the location coordinates of the unknown node,

The ordinate representing the location coordinates of the unknown node.

Specifically, the method for removing cloned nodes is as follows:

(1) Assuming that there are p, p=m+n nodes in the communication range of the unknown node, select p-1 nodes from the p nodes as a group for calculating the position of the unknown node, and for each group obtained The position of the unknown node is calculated and the mean square error of the position of the unknown node is calculated. There are p mean square errors in total, which are recorded as

将M与γ做比较，若M<γ，则无线传感器网络中没有克隆节点，停止算法；若M>γ，则无线传感器网络中有克隆节点，从均方误差最小的一组节点中随机剔除一个节点；(2) Select the smallest set of mean square errors in Y through the bubble algorithm, denoted as

Compare M with γ. If M<γ, there is no clone node in the wireless sensor network, and the algorithm stops; if M>γ, there is a clone node in the wireless sensor network, and it is randomly selected from the group of nodes with the smallest mean square error. a node;

(3) Select p-2 nodes from the p-1 nodes as a group for calculating the position of the unknown node, and continue to perform the above steps (1) and (2) until the minimum set of mean square errors M If it is less than γ, stop the algorithm and complete the elimination of clone nodes.

For example: randomly remove a node from the node information set L, and generate a new set with a total of q groups, one of which is:

选出选出均方误差最小的一组与γ进行比较。如果均方误差小于γ，则停止剔除节点。如果均方误差大于γ，则从均方误差最小的集合中，再次随机减少一个节点。继续之前的操作，直至均方误差小于γ。The data of the q group set is brought into the calculation of the mean square error of the unknown node, and a set of mean square error is obtained as

The group with the smallest mean square error is selected and compared with γ. Stop culling nodes if the mean squared error is less than γ. If the mean squared error is greater than γ, from the set with the smallest mean squared error, one node is randomly reduced again. Continue the previous operation until the mean squared error is less than γ.

The method of minimum mean square error is used to eliminate clone nodes, a node is randomly selected from a set of node information, and the mean square error of unknown nodes is calculated. When the removed node is a clone node, the mean square error of the unknown node will be reduced. Then, from a group of nodes with the smallest mean square error, a node is randomly removed, and then the mean square error of the unknown node is calculated until the minimum mean square error is less than γ, so as to ensure that the unknown node is positioned in a safe environment, and the unknown nodes are located in a safe environment. Node positioning can effectively improve the positioning accuracy of unknown nodes.

In order to further illustrate the advantages and effectiveness of the above method of the present invention, the present invention will be further described below with reference to the accompanying drawings and embodiments.

Embodiment: A batch of beacon nodes and unknown nodes are randomly deployed in the wireless sensor network, U is an unknown node, and B1, B2, B3, B4, and B5 are beacon nodes. The beacon node obtains its own location coordinate information in advance, and provides positioning services for unknown nodes. Unknown nodes need to obtain their own position coordinates through positioning technology. B2' and B4' are cloned nodes captured by clone attack B2 and B4 respectively. They participate in the positioning process of unknown nodes by obtaining the ID and location coordinate information of beacon nodes, which can affect the positioning accuracy of unknown nodes. Each node can communicate with each other of information. Each beacon node has a unique ID, and the clone node, like the beacon node ID, can also participate in the process of locating unknown nodes. The communication radius of unknown node, beacon node and clone node are all R, and d2', d2, d4', d4 are the distances from U to B2', B2, B4', B4, respectively. The problem of data loss in communication between nodes is not considered.

When the unknown node U sends a positioning request, both the beacon node and the clone node will send the position coordinate information after receiving the broadcast. The theoretical model used by the node for wireless signal transmission is the attenuation model RSSI(d)=RSSI(d ₀ )-10αlog(d/d ₀ )+P _n , where RSSI represents the signal strength value of the unknown node receiving the beacon node, d represents the distance between the unknown node and the beacon node, d ₀ is the reference distance, α represents the path loss index, and P _n represents a Gaussian random variable with a mean value of 0. Thus, the distances d1, d2', d3, d4', and d5 from the beacon node to the unknown node U are calculated. By calculating the distance from the beacon node to the unknown node, combined with the position coordinates of the beacon node, the unknown node uses the maximum likelihood estimation method to obtain its own estimated position information. When the wireless sensor network is in a safe state, the position coordinates of the unknown nodes obtained by using the maximum likelihood estimation method are relatively concentrated on the two-dimensional plane, which is expressed as a dense area centered on the true position of the unknown node, and the average value of the unknown node is obtained. The square error values are the same. If there are clone nodes in the wireless sensor network, the calculated mean square error value of the unknown node is inconsistent, and it is greater than the mean square error value of the unknown node in the safe state. Referring to Figure 2, the position coordinates of B1, B2', B3, B4', B5 and the distance to the unknown node are brought into formula (1), the position coordinates of the unknown node are calculated, and then the calculated result is brought into the formula ( In 5), the mean square error of the unknown node is obtained, and by comparing with γ, it is judged whether there is a clone node in the wireless sensor network. In this example, the position coordinate information sent by B2' and B4' is the position coordinate information of B2 and B4, so the mean square error of the unknown node U is greater than the upper limit of the error of the experimental statistics, that is, the mean square error threshold γ, so as to judge the group The beacon node set contains clone nodes, and the method of minimum mean square error needs to be further used to eliminate clone nodes.

选出均方误差最小的一组与γ进行比较。如果均方误差小于γ，则停止剔除节点。如果均方误差大于γ，则从均方误差最小的集合中，再次随机减少一个节点，重复之前的操作步骤，直至均方误差小于γ。A node is randomly selected from a set of node information, and the mean square error of the unknown node is calculated. When the removed node is a clone node, the mean square error of the unknown node will be reduced. Then, from a group of nodes with the smallest mean square error, a node is randomly removed, and the same operation is performed until the smallest mean square error is less than γ. In this example, a node is randomly selected from the beacon node set L={B1, B2', B3, B4', B5}, and a total of 5 new sets are generated, which are L1={B2', B3, B4',B5}L2={B1,B3,B4',B5}, L3={B1,B2',B4',B5}, L4={B1,B2',B3,B5}, L5={B1, B2', B3, B4'}, bring the 5 sets of data into the mean square error calculation of the unknown node, and get the mean square error as

The group with the smallest mean square error is selected for comparison with γ. Stop culling nodes if the mean squared error is less than γ. If the mean square error is greater than γ, from the set with the smallest mean square error, one node is randomly reduced again, and the previous operation steps are repeated until the mean square error is less than γ.

The clone attack is detected by the consistency of the mean square error, and then the clone node is eliminated by the method of minimum mean square error to ensure that the location of the unknown node is in a safe environment.

Referring to Figure 3 and Figure 4, the more clone nodes contained in the wireless sensor network, the greater the impact on the location of unknown nodes, and the lower the location accuracy. Specifically, continue to refer to Fig. 3, the more the number of clone nodes, the greater the influence on the mean square error of the estimated position of the unknown node. In the case of the same number of beacon nodes, the more the number of clone nodes, the greater the estimated value of the unknown node. The larger the mean squared error of the location. Continuing to refer to Figure 4, the more the number of clone nodes, the greater the impact on the positioning error of the unknown node. In the case of the same number of beacon nodes, the more the number of clone nodes, the greater the positioning error of the unknown node, and the greater the positioning error of the unknown node. the lower the accuracy.

Referring to Figure 5 and Figure 6, as the distance from the clone node to the unknown node in the wireless sensor network increases, the mean square error of the estimated position of the unknown node is larger, and the positioning error of the unknown node is larger.

Referring to FIG. 7 , the above-mentioned security positioning method, the positioning method with cloning attack and the positioning method without cloning attack of the present invention are used to locate the unknown node of the wireless sensor network. With the increase of the number of beacon nodes, the positioning with cloning attack is adopted. The method and the positioning method without cloning attack, the positioning error of the unknown node remains basically unchanged, and the positioning error of the unknown node without the clone attack is significantly smaller than the positioning error of the unknown node with the clone attack. With the above-mentioned security positioning method of the present invention, with the increase of the number of beacon nodes, the positioning error of the unknown node is significantly reduced, and compared with the positioning method with clone attack and the positioning method without clone attack, the positioning error of the unknown node is significantly reduced. Significantly smaller than the above two methods. It should be noted that, although the number of beacon nodes is less than 20, the positioning error of the unknown node using the above-mentioned security positioning method of the present invention is greater than the positioning error of the unknown node of the positioning method without cloning attack, but the difference is not obvious. However, when When there are more than 20 beacon nodes, with the increase of beacon nodes, the positioning error of the unknown node using the above-mentioned secure positioning method of the present invention is obviously smaller than that of the unknown node of the positioning method without cloning attack.

As can be seen from the above, the wireless sensor network security positioning method for cloning attacks provided by the present invention can effectively detect clone nodes, and eliminate clone nodes, ensure that unknown nodes are located in a safe environment, and can greatly reduce the number of clone nodes. The influence of unknown node positioning improves positioning accuracy and is more effective than existing methods.

The above-mentioned embodiments are only used to illustrate the present invention for convenience, and are not intended to limit the scope of protection of the present invention. Within the scope of the technical solutions described in the present invention, various simple deformations and modifications made by those skilled in the art shall be included in the above descriptions. patent application.

Claims (2)

1. A wireless sensor network security positioning method for cloning attack, wherein the wireless sensor network comprises m, m≥3 beacon nodes, multiple unknown nodes and n,0≤n＜m clone nodes , each beacon node has a unique ID, and each beacon node knows its own position coordinates, the communication radius of the beacon node, unknown node and clone node is R, no communication data is lost between nodes, m The position coordinates of the beacon nodes are (x ₁ , y ₁ ), (x ₂ , y ₂ ),..., (x _m , y _m ), and the distances from the unknown nodes to the beacon nodes are d ₁ , d ₂ ,...,d _m ; the method comprises the following steps: (1) The beacon node periodically sends its own ID and location coordinates to its surrounding nodes. When the known unknown node receives the signal strength value sent by the beacon node, the attenuation model of the signal strength value is used to calculate the distance between the beacon node and the unknown node. The distance of the node; through the calculated distance from the beacon node to the unknown node, combined with the position coordinates of the beacon node, the estimated position of the unknown node is obtained; (2) Use the mean square error consistency to detect whether there is a clone attack in the wireless sensor network according to the mean square error of the estimated position of the unknown node. If there is no clone attack, the estimated position of the unknown node obtained in step (1) is unknown. The safe positioning position of the node; if there is a cloning attack, remove the cloned node until the minimum mean square error of the unknown node is less than the set mean square error threshold γ, repeat the steps of step (1), and the estimated position of the unknown node obtained is unknown. The safe positioning position of the node; the specific method to detect whether there is a clone attack in the wireless sensor network according to the mean square error of the estimated position of the unknown node by using the mean square error consistency is: The position coordinates of the estimated position obtained by the unknown node are relatively concentrated on the two-dimensional plane, which is represented as a dense area centered on the real position of the unknown node, and the mean square error of the unknown node is consistent. If there are clones in the wireless sensor network node, the calculated mean square error value of the unknown node is inconsistent, and is greater than the mean square error value of the unknown node in the safe state; the mean square error of the unknown node is calculated by formula (5), and formula (5) is expressed as:

In the formula,

represents the mean square error of the unknown node, x _j represents the abscissa of the position coordinate of the jth beacon node, y _j represents the ordinate of the position coordinate of the jth beacon node,

the abscissa representing the location coordinates of the unknown node,

The ordinate representing the location coordinates of the unknown node; The culling method of cloned nodes is: (1) Assuming that there are p, p=m+n nodes in the communication range of the unknown node, select p-1 nodes from the p nodes as a group for calculating the position of the unknown node, and for each group obtained The position of the unknown node is calculated and the mean square error of the position of the unknown node is calculated. There are p mean square errors in total, which are recorded as

(2) Select the smallest set of mean square errors in Y, denoted as

Compare M with γ, if M<γ, there is no clone node in the wireless sensor network; if M>γ, there is a clone node in the wireless sensor network, and a node is randomly selected from a group of nodes with the smallest mean square error; (3) Select p-2 nodes from the p-1 nodes as a group for calculating the position of the unknown node, and continue to perform the above steps (1) and (2) until the minimum set of mean square errors M If it is less than γ, stop the algorithm and complete the elimination of clone nodes. 2 . The wireless sensor network security positioning method for cloning attack according to claim 1 , wherein the attenuation model of the signal strength value is expressed as: RSSI(d)=RSSI(d ₀ )-10αlog(d/d ₀ . 3 . )+P _n , where RSSI represents the signal strength value of the unknown node receiving the beacon node, d represents the distance between the unknown node and the beacon node, d ₀ is the reference distance, α represents the path loss index, and P _n represents the Gaussian with mean 0 Random variable; Assuming that the position coordinates of the unknown node are (x, y), the formula for calculating the position coordinates of the unknown node is expressed as:

From the first equation of formula (1) to the m-1th equation, subtract the mth equation in turn to obtain a linear equation, where:

In the formula, A and b represent the coefficient matrix, and X represents the actual position coordinates of the unknown node; Using the maximum likelihood estimation method, the estimated position coordinates of the unknown nodes are calculated as:

in,

Represents the estimated location coordinates of the unknown node.

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