CN111801953A - Positioning optimization method, device, device and storage medium for wireless sensor network - Google Patents

Abstract

Disclosed herein are a method, an apparatus, a device and a storage medium for location optimization of a wireless sensor network, wherein the method comprises: acquiring first receiver noise extracted by a target node when receiving a challenge signal and second receiver noise extracted by an anchor point when receiving a response signal; determining the target distance between the anchor point and the target node; determining a target detection threshold value according to a set upper limit value of the false alarm probability; determining a detection result of the ranging augmentation attack according to the first receiver noise, the second receiver noise and a target detection threshold; if the detection result of the ranging increase attack is that the ranging increase attack does not exist, positioning the target node according to the target distance; otherwise, the target distance is discarded.

Description

Positioning optimization method, device, device and storage medium for wireless sensor network

technical field

The embodiments of the present application relate to the technical field of wireless network communications, for example, to a method, apparatus, device, and storage medium for positioning optimization of a wireless sensor network.

Background technique

Wireless sensor networks have a wide range of applications in military and civilian fields, and the location information of sensor nodes is very important for environmental monitoring and target node tracking. Although the location information of sensor nodes can be provided through a Global Positioning System (Global Positioning System, GPS), the performance of GPS is very sensitive to the environment, and the cost is too high for low-cost sensor nodes. Therefore, in some applications, the system locates the target node through wireless transmission between anchor target nodes, such as based on Received Signal Strength (RSS), Time Of Arrival (ToA), time difference of arrival (based on target radiation source) and angle of arrival (Angle of Arrival, AoA), etc.

The security of wireless systems is an important issue, and the security loopholes caused by the openness of wireless systems, the distributed nature of sensor positioning schemes, and the possible existence of multiple attackers (especially coordinated attackers) make it impossible to guarantee wireless sensor networks. The security of the positioning scheme is challenging. The attack defense scheme for the positioning scheme often introduces high communication overhead, and its security depends on the attacker's ability. The high communication overhead of the traditional scheme leads to the following limitations. First, the battery life of all sensor nodes needs to be high enough; second, the storage space of each sensor node must be large enough; third, in the case of mobile sensor nodes, the timeliness is relatively high. Difference. In addition, if the attacker has enough energy to launch more attacks, even if a high communication overhead is introduced, the traditional scheme will fail. To sum up, the solutions for ensuring positioning security in the wireless sensor network in the related art cannot meet the requirement of flexibility.

SUMMARY OF THE INVENTION

The embodiments of the present application provide a positioning optimization method, device, device, and storage medium for a wireless sensor network, so as to optimize the positioning optimization scheme of the wireless sensor, reduce communication overhead, and improve flexibility.

An embodiment of the present application provides a method for optimizing the positioning of a wireless sensor network, including:

obtaining the first receiver noise extracted by the target node when receiving the challenge signal, and the second receiver noise extracted by the anchor point when receiving the response signal; and determining the target distance between the anchor point and the target node;

Determine the target detection threshold according to the set false alarm probability upper limit;

determining a detection result of a ranging increase attack according to the first receiver noise, the second receiver noise, and the target detection threshold;

If the detection result of the range increase attack is that there is no range increase attack, the target node is located according to the target distance; otherwise, the target distance is discarded.

The embodiment of the present application also provides a positioning optimization device for a wireless sensor network, including:

The information acquisition module is used to acquire the first receiver noise extracted by the target node when receiving the challenge signal, and the second receiver noise extracted by the anchor point when receiving the response signal; and determine the difference between the anchor point and the target node target distance;

The detection threshold determination module is used to determine the target detection threshold according to the set false alarm probability upper limit value;

an attack detection module, configured to determine the detection result of the ranging attack according to the first receiver noise, the second receiver noise and the target detection threshold;

A positioning module, configured to locate the target node according to the target distance if the detection result of the range increase attack is that there is no range increase attack; otherwise, discard the target distance.

The embodiment of the present application also provides a device, the device includes:

one or more processors;

a storage device for storing one or more programs;

When the one or more programs are executed by the one or more processors, the one or more processors implement the above-mentioned method for optimizing the positioning of the wireless sensor network.

Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, implements the above-mentioned method for positioning optimization of a wireless sensor network.

In the wireless sensor positioning optimization solution provided by the embodiments of the present application, the first receiver noise extracted by the target node when receiving the challenge signal and the second receiver noise extracted by the anchor point when receiving the response signal are obtained; and the anchor point and The target distance of the target node; the target detection threshold is determined according to the upper limit of the false alarm probability; the detection result of the ranging attack is determined according to the noise of the first receiver, the noise of the second receiver and the target detection threshold; If the detection result of the increase attack is that there is no range increase attack, the target node is located according to the target distance; otherwise, the target distance is discarded. By adopting the above technical scheme, by extracting the receiver noise in the wireless transmission process, and according to the receiver noise and setting the upper limit of the false alarm probability, the detection of the range increase attack can be realized by one measurement. For sensor node positioning, since the upper limit of false alarm probability can be flexibly adjusted based on the actual situation, the flexibility of detection threshold is improved, communication overhead is saved on the basis of ensuring safe positioning, and the detection of range-increasing attacks is improved. flexibility.

Description of drawings

FIG. 1 is a flowchart of a method for positioning optimization of a wireless sensor network according to an embodiment of the present application;

FIG. 2 is a schematic diagram of a positioning optimization method for a wireless sensor network provided by an embodiment of the present application;

3 is a schematic diagram of a related art positioning method provided by an embodiment of the present application;

FIG. 4 is a schematic diagram of a ranging attack provided by an embodiment of the present application;

FIG. 5 is a schematic diagram of the location of a range-enhancing attack provided by an embodiment of the present application;

6 is a schematic diagram of bidirectional positioning provided by an embodiment of the present application;

FIG. 7 is a flowchart of another wireless sensor network positioning optimization method provided by an embodiment of the present application;

FIG. 8 is a schematic diagram of a wireless sensor network system according to an embodiment of the present application;

Fig. 9 is a kind of comparative schematic diagram of experiment and theory provided by the embodiment of this application;

10 is a schematic diagram of the relationship between a detection performance and the number of measurements provided by an embodiment of the application;

11 is a schematic diagram of the relationship between a communication overhead and the number of anchor points according to an embodiment of the present application;

12 is a schematic diagram of the relationship between a communication overhead and the number of measurements provided by an embodiment of the present application;

13 is a schematic diagram of the relationship between a performance-overhead ratio and the number of measurements provided by an embodiment of the present application;

FIG. 14 is a schematic structural diagram of an apparatus for positioning optimization of a wireless sensor network according to an embodiment of the present application;

FIG. 15 is a schematic structural diagram of a device provided by an embodiment of the present application.

Detailed ways

The present application will be described below with reference to the accompanying drawings and embodiments. The specific embodiments described herein are only used to explain the present application, but not to limit the present application. For convenience of description, the drawings only show some but not all structures related to the present application.

Before discussing the exemplary embodiments, it should be mentioned that some exemplary embodiments are described as processes or methods depicted as flowcharts. Although the flowchart depicts the steps as a sequential process, many of the steps may be performed in parallel, concurrently, or concurrently. Furthermore, the order of the steps can be rearranged. The process may be terminated when its operation is complete, but may also have additional steps not included in the figures. The processes may correspond to methods, functions, procedures, subroutines, subroutines, and the like.

FIG. 1 is a flowchart of a method for positioning optimization of a wireless sensor network provided by an embodiment of the present application. This embodiment is applicable to the situation of realizing safe positioning of wireless sensors, and the method can be executed by a positioning optimization device of a wireless sensor network, The apparatus may be implemented in software and/or hardware, and the apparatus may be configured in an electronic device, such as a server or a terminal device. As shown in Figure 1, the method may include:

S110. Acquire the first receiver noise extracted by the target node when receiving the challenge signal, and the second receiver noise extracted by the anchor point when receiving the response signal; and determine the target distance between the anchor point and the target node.

Among them, the target node and the anchor point refer to the sensor node in the wireless sensor network, and the anchor point is used to determine the position of the target node. In this embodiment, it is assumed that the position of the anchor point can be pre-determined by the GPS system or other methods at any time and place. Sure. The challenge signal is the signal sent by the anchor to the target node, and the response signal is the signal returned by the target node to the anchor after receiving the challenge signal. The first receiver noise is the receiver noise extracted when the target node receives the challenge signal, and the second receiver noise is the receiver noise extracted when the anchor point receives the response signal.

In this embodiment, the anchor point can send a challenge signal to the target node, and after the target node receives the challenge signal, it extracts the first receiver noise at this time; the target node generates a response signal according to the first receiver noise and the challenge signal, and The response signal is sent to the anchor; after the anchor receives the response signal, the second receiver noise can be extracted. After the anchor point receives the response signal, the time interval can be recorded, and the target distance between the anchor point and the target node can be determined according to the time interval, that is, the ranging is realized. Alternatively, the positioning optimization device of the wireless sensor network can also obtain the time interval recorded by the anchor point, and then determine the target distance between the anchor point and the target node, that is, to achieve ranging.

目标节点S生成响应信号，并将响应信号返回给锚点A；锚点A在t₂接收到响应信号，记录时间间隔为τ_AS＝t₂-t₁，以备后续进行定位，并估计第二接收机噪声

2 is a schematic diagram of a method for positioning optimization of a wireless sensor network according to an embodiment of the present application. In Figure 2, the anchor point A sends a challenge signal to the target node S, and the target node S receives the challenge signal D at time _t1 , and estimates the first receiver noise

The target node S generates a response signal and returns the response signal to the anchor point A; the anchor point A receives the response signal at t ₂ , and the recording time interval is τ _AS =t ₂ -t ₁ for subsequent positioning and estimation of the first Two receiver noise

In the traditional scheme, the distance between the anchor point and the target node is estimated by continuously measuring multiple arrival times and storing the median value. A secure positioning scheme is proposed, as shown in Figure 3. 3 is a schematic diagram of a positioning method of a related art provided by an embodiment of the present application. It is assumed that the key K is shared between all anchor nodes and the target node, and the message integrity code technology is used to ensure security. M is encrypted with g _K (M), g( ) represents the hash function and K is the key, external attackers may know the details of g( ), but do not know the key K, which has two functions: one is To determine the source of M, the second is to ensure the integrity of M to prevent tampering attacks.

The traditional scheme requires L measurements, each measurement consists of three wireless transmissions, that is, L≥3, as shown in Figure 3. In each measurement, first the anchor point A sends a challenge signal consisting of an l-bit random number D to the target node S; the target node S receives the challenge signal at time _t1 , and then extracts the random number D, and the target node S sends 2l The response signal of -bit D||B is sent to anchor point A, anchor point A receives the response signal at time t ₂ , || represents the message connection operator, and B is also an l-bit random number; then anchor point A will The elapsed time was recorded as τ _AS = t ₂ -t ₁ and t _AS for the bidirectional ToA was calculated. At the same time, the anchor point A extracts D||B from the received response signal, and calculates the value of v=g _K (D||B); the target node S sends the MIC signal g _K (D||B) to the Anchor point A.

The traditional scheme detects range reduction and range increase attacks in two consecutive steps. In the first step, if the received MIC is the same as the value of v, the detection of the range reduction attack has passed; in the second step, in the After continuous measurement of multiple ToAs, the prior scheme uses the median of the measurement times as the final measurement value to resist range-enhancing attacks. The resistance of the traditional scheme to the range increase attack depends on the number of attacks M. If M≤(L-1)/2, the range increase attack can be successfully detected; otherwise, its security cannot be guaranteed. While both types of attacks pass the detection, anchor A can accept t _AS as a legitimate ToA and store it as useful positioning information to obtain the actual location of the target node. For a wireless sensor network including N _A anchor points, the communication overhead of the traditional scheme is 3L N _A , the number 3 means that each measurement contains three wireless transmissions, and L means the number of measurements, so when N _A or L increases, the traditional scheme increased communication overhead. In addition, the traditional scheme has low flexibility in detecting range-enhancing attacks, regardless of changes in the actual situation, simply compare the MIC of each measurement with v to determine whether to retain the measurement results, and then take the median of multiple measurement results. number as the final result. Based on the above technical problems, in this embodiment, it is considered that when an external attacker forwards the challenge signal, additional receiver noise will inevitably be introduced, the receiver noise is used to perform attack detection before security positioning, and the target is detected based on the attack detection result. Secure positioning of nodes to reduce communication overhead and improve flexibility.

S120. Determine the target detection threshold according to the upper limit value of the set false alarm probability.

Among them, it is assumed that H ₀ indicates that there is no ranging attack, and H ₁ indicates that there is a ranging attack. Accepting the assumption H ₁ when H ₀ is true is called the probability of false alarm (PFA), that is, P _fa =P{H ₁ |H ₀ }. The upper limit value of the false alarm probability is set as the upper limit value of the false alarm probability preset by the user according to the current actual demand and the actual situation when there is a channel estimation error, which can be flexibly changed based on the user's choice. The target detection threshold is a threshold used to detect range-enhancing attacks. There is a correlation between the target detection threshold and the upper limit of the false alarm probability. The target detection threshold can be determined based on the upper limit of the false alarm probability. Therefore, when the upper limit of the false alarm probability can be set flexibly according to the actual situation, the target detection threshold can also be flexibly changed.

In this embodiment, two situations are considered when determining the target detection threshold, one is a situation where there is a channel estimation error, and the other is a situation where there is no channel estimation error.

其中，P_fa表示误报概率，θ表示目标检测阈值，

表示响应信号或挑战信号的方差，

表示信道估计误差的方差。Determining the target detection threshold according to the set false alarm probability upper limit value may include: determining the target detection threshold value according to the set false alarm probability upper limit value and a predetermined detection threshold expression. In one embodiment, the detection threshold expression is:

Among them, P _fa represents the probability of false positives, θ represents the target detection threshold,

represents the variance of the response signal or challenge signal,

Represents the variance of the channel estimation error.

其中，P_fa表示误报概率，θ表示目标检测阈值，H₁表示存在测距增大攻击的情况，H₀表示无测距增大攻击的情况，

表示响应信号或挑战信号的方差，

表示信道估计误差的方差。The target detection threshold can be determined based on the false positive probability expression, and the false positive probability expression is:

Among them, P _fa represents the probability of false positives, θ represents the target detection threshold, H ₁ represents the presence of a ranging attack, H ₀ represents no ranging attack,

represents the variance of the response signal or challenge signal,

Represents the variance of the channel estimation error.

所有的锚点和目标节点都有相同的接收机噪声，即

但是，恶意节点的传输功率和接收噪声不同，增加了硬件成本，恶意节点的传输功率由G_E确定，n_E的噪声方差为

其中β表示恶意节点的硬件性能，β＝1表示恶意节点的硬件性能与锚节点和目标节点相似；β＜1表示恶意节点硬件性能较好，但硬件成本较高；β＞1表示恶意节点的硬件性能较差，但硬件成本较低。基于S110中第一接收机噪声和第二接收机噪声的表达式，将信道估计误差的方差表示为

和

其中α表示所采用的信道估计算法的性能，信道估计误差由采用的信道估计算法和接收机噪声共同决定。When there is a channel estimation error, it is assumed that the transmission power of the challenge signal and the response signal are the same, i.e.

All anchor and target nodes have the same receiver noise, i.e.

However, the transmission power of the malicious node is different from the received noise, which increases the hardware cost. The transmission power of the malicious node is determined by G _E , and the noise variance of n _E is

Among them, β represents the hardware performance of the malicious node, β=1 indicates that the hardware performance of the malicious node is similar to that of the anchor node and the target node; β<1 indicates that the hardware performance of the malicious node is better, but the hardware cost is high; The hardware performance is poor, but the hardware cost is lower. Based on the expressions of the first receiver noise and the second receiver noise in S110, the variance of the channel estimation error is expressed as

and

Among them, α represents the performance of the adopted channel estimation algorithm, and the channel estimation error is jointly determined by the adopted channel estimation algorithm and the receiver noise.

确定响应信号或挑战信号的方差、信道估计误差的方差以及设定误报概率上限值之后，代入上述公式，即可确定目标检测阈值。The target detection threshold can be determined based on the false positive probability expression

After determining the variance of the response signal or the challenge signal, the variance of the channel estimation error, and setting the upper limit of the false alarm probability, the target detection threshold can be determined by substituting the above formula.

Optionally, determining the target detection threshold according to the set false alarm probability upper limit value may include: setting both the false alarm probability upper limit value and the target detection threshold value to zero when there is no channel estimation error. If all channel estimation errors are ignored, the false alarm probability P _fa =P{H ₁ |H ₀ }=0, and the target detection threshold θ=0.

In addition, when there is a channel estimation error, after determining the target detection threshold according to the upper limit value of the false alarm probability and the predetermined detection threshold expression, it also includes: according to the target detection threshold, the false alarm probability expression and the detection threshold A probability expression that determines the detection probability to validate the target detection threshold based on the detection probability.

Accepting the hypothesis H ₁ when H ₁ is true is called the probability of detection (PD), ie P _d =P{H ₁ |H ₁ }. The optimal threshold of detection probability can be determined by the calculation of the Neyman-Pearson theorem. The detection probability expression can be expressed as

After the detection probability is determined according to the target detection threshold, the false alarm probability expression and the detection probability expression, according to the detection probability and the optimal detection probability threshold, it can be verified that the performance of the current target detection threshold is better, that is, it is determined that the current environment is suitable for this implementation. method used in the example.

S130. Determine the detection result of the ranging attack according to the noise of the first receiver, the noise of the second receiver, and the target detection threshold.

是目标节点的估计位置，A₁表示锚点，E₁和E₂表示恶意节点，恶意节点的目的是破坏定位过程或降低定位精度。The positioning method used in this embodiment is the two-way Time Of Arrival (ToA) algorithm, and in the two-way ToA technology, there are two loopholes: distance reduction attack and range increase attack. Range increases attack. Two malicious nodes cooperate to launch an attack, as shown in FIG. 4 . FIG. 4 is a schematic diagram of a ranging attack provided by an embodiment of the present application. FIG. 5 shows the effect of the attack, and FIG. 5 is a schematic diagram of the location of a range-enhancing attack provided by an embodiment of the present application. In Figures 4 and 5, S1 is the actual position _of the target node,

is the estimated location of the target node, A ₁ represents the anchor point, E ₁ and E ₂ represent malicious nodes, and the purpose of malicious nodes is to disrupt the localization process or reduce the localization accuracy.

E₂发射干扰信号S₁，然后E₁收到

表示为

在第二阶段，E₂保持沉默和E₁直接发送

给S₁，附带增益G_E，接收信号在S₁表示为

是来自E₁到S₁的信道响应。然后S₁发送响应信号

给A₁。因此A₁接收响应信号需要更长的时间，A₁与无攻击时相比，将获得更长的双向ToA值。因此A₁得到距离增大的估计值，如图5所示。最后，估计了S₁的错误位置。In the range augmentation attack, as shown in Figure 4, E2 has different roles in _two stages. In the _first stage, when A1 sends a challenge signal

E ₂ transmits interfering signal S ₁ , which is then received by E ₁

Expressed as

_In the second stage, _E2 keeps silent and E1 sends directly

Given S ₁ , with gain G _E , the received signal at S ₁ is expressed as

is the channel response from _E1 to _S1 . Then S1 sends _a response signal

give A ₁ . Therefore, it takes a longer time for A ₁ to receive the response signal, and A ₁ will obtain a longer bidirectional ToA value than when there is no attack. Therefore A1 gets _an estimate of the increase in distance, as shown in Figure 5. Finally, the error location _of S1 is estimated.

Determining the detection result of the ranging attack according to the first receiver noise, the second receiver noise, and the target detection threshold may include: determining a variance difference between the noise variance of the second receiver and the noise variance of the first receiver; The comparison result of the difference value and the target detection threshold value determines the detection result of the range-enhancing attack. In one embodiment, determining the detection result of the ranging attack according to the comparison result of the variance difference and the target detection threshold, including: if the variance difference is less than or equal to the target detection threshold, then determining the detection result of the ranging attack It means that there is no ranging attack; otherwise, the detection result of the ranging attack is that there is a ranging attack.

和

在H₀时，目标节点S通过信道估计算法和恢复消息

获得估计的信道响应

因为恢复的错误可以通过调制和信道编码来纠正，本实施例中假设消息可以完全恢复，即

目标节点S提取接收机噪声为

目标节点S计算它的方差

在H₁时，目标节点S得到信道响应为

提取的接收机噪声为

目标节点S计算它的方差

之后，由于本实施例中以假设锚点A发送挑战信号给目标节点S时有攻击，而目标节点S返回响应信号时无攻击，因此锚点A得到信道响应为

提取的接收机噪声为

锚点A计算它的方差

In this embodiment, it is assumed that H ₀ indicates that there is no ranging attack, and H ₁ indicates that there is a ranging attack. The challenge signal received by the target node S is expressed as H ₀ and H ₁ , respectively

and

At H ₀ , the target node S recovers the message through the channel estimation algorithm and

Get the estimated channel response

Since the recovered error can be corrected by modulation and channel coding, it is assumed in this embodiment that the message can be completely recovered, i.e.

The target node S extracts the receiver noise as

The target node S computes its variance

At _H1 , the target node S gets the channel response as

The extracted receiver noise is

The target node S computes its variance

After that, since it is assumed in this embodiment that there is an attack when the anchor point A sends the challenge signal to the target node S, and the target node S has no attack when it returns the response signal, the channel response obtained by the anchor point A is:

The extracted receiver noise is

Anchor A calculates its variance

表示绝对值运算符。当存在信道估计误差的情况下，在H₀和H₁分别重写为

和

其中

和

基于引理1，误报概率

根据奈曼-皮尔逊定理，通过设置最大值来计算误报概率的最大阈值，本实施例中通过ε表示该误报概率的最大阈值，P_fa≤ε。根据引理2，可以得到检测概率的表达式。当不存在信道估计误差的情况下，在H₀和H₁分别重写为

和

由于

|h_ES|²是参数为

指数分布的随机变量。即

因此目标检测阈值设为θ＝0。因此P_fa＝P{δ＞θ°|H₀}＝0和

The variance difference can be

Represents an absolute value operator. When there is a channel estimation error, H ₀ and H ₁ are rewritten as

and

in

and

Based on Lemma 1, the false positive probability

According to the Neyman-Pearson theorem, the maximum threshold of the false alarm probability is calculated by setting the maximum value. In this embodiment, ε represents the maximum threshold of the false alarm probability, and P _fa ≤ε. According to Lemma 2, the expression of detection probability can be obtained. When there is no channel estimation error, H ₀ and H ₁ are rewritten as

and

because

|h _ES | ² is the parameter for

An exponentially distributed random variable. which is

Therefore, the target detection threshold is set to θ=0. Therefore P _fa =P{δ>θ°|H ₀ }=0 and

When δ≤θ, it can be determined that the detection result of the ranging attack is that there is no ranging attack; otherwise, the detection result of the ranging attack is that there is a ranging attack. where θ represents the target detection threshold.

In this embodiment, each measurement includes two wireless transmissions, by appropriately increasing the value of the duration after the last bit of the challenge signal reaches the antenna of the target node until the first bit of the response signal is transmitted from the antenna of the target node, A large constant is obtained, which is large enough to complete all operations; and the attack detection method in this embodiment only needs one measurement. For _a wireless sensor network, the communication overhead is _2NA , where NA is the number of anchor points in the wireless sensor network. Therefore, compared with traditional schemes, the present scheme saves communication overhead, especially in the case of large-scale wireless sensor networks or powerful external attackers. Moreover, when there is a channel estimation error, the upper limit of the false alarm probability can be set flexibly according to the actual situation, and the target detection threshold can also be changed flexibly, which improves flexibility on the basis of saving communication overhead.

In this embodiment, while determining the detection result of the range increase attack, the detection result of the range reduction attack can also be obtained by introducing the receiver noise variance to detect the range reduction attack.

S140. If the detection result of the range increase attack is that there is no range increase attack, locate the target node according to the target distance; otherwise, discard the target distance.

If only the range-increasing attack is currently considered, the target node can be located only according to the detection result of the range-increasing attack. That is, if the attack detection result is that there is no ranging attack, the two-way arrival time algorithm is used to locate the target node according to the target distance; if the attack detection result is that there is a ranging attack, the target distance is discarded. After discarding the target distance, it is necessary to check the malicious nodes attacking the wireless sensor network to eliminate the range increase attack, and then locate the target node until the attack detection result is that there is no range increase attack.

If it is currently necessary to consider both the range-increasing attack and the range-reducing attack, before locating the target node according to the target distance, it may also include: determining the detection result of the range-reducing attack; correspondingly, if the range-increasing attack is When the detection result is that there is no range increase attack and the detection result of the range reduction attack is that there is no range reduction attack, the target node is located according to the target distance; otherwise, the target distance is discarded. If the attack detection result is that there is a range reduction attack or a range increase attack, it is necessary to check the malicious nodes that attack the wireless sensor network to eliminate the attack, until the attack detection result is that there is no distance reduction attack or increase attack. target node for positioning.

The two-way time of arrival algorithm is an algorithm for locating sensor nodes in wireless sensor networks. Three types of sensor nodes can be included in a wireless sensor network: anchors, target nodes and malicious nodes. The role of the anchor point is to determine the location of the target node, while the purpose of the malicious node is to disrupt the localization process or reduce the localization accuracy. In order to determine the 2D position of the target node, the number of anchor points should be greater than 3. The more anchor points, the higher the corresponding positioning accuracy, but at the same time increase the communication overhead, so the number of anchor points can be set according to the actual situation.

N_S个目标节点，表示为

和N_E个恶意节点，表示为

其中N_A≥3。假设N_A＝3，N_S＝1和N_E＝2，A₁在时间t₁首先发送一个挑战信号

给S₁。S₁收到的信号表示为

其中

和

分别是A₁到S₁的信道响应和S₁提取的接收端噪声，假设所有的信道响应都建模为零均值复高斯随机变量(RVs)，即

其中

和d是发射机和接收机之间的距离，λ＝c/f_c是发射信号的波长，c是光速，f_c是发射信号的载波频率。G_t和G_r分别是发射天线增益和接收天线增益。假设接收机噪声也被建模为零均值复高斯随机变量，如

是基于硬件的。接收到的信噪比(Signal Noise Ratio，SNR)表示为

其中P_t表示传输功率。In wireless sensor networks, all sensor nodes are randomly deployed on a plane, and the localization process of the target node is usually completed in the network initialization phase. Suppose there are N _A anchors, denoted as

N _S target nodes, denoted as

and N _E malicious nodes, denoted as

where N _A ≥ 3. Assuming NA ₌ 3, _NS = 1 and _{NE =} 2, A ₁ first sends a challenge signal at time t ₁

give S ₁ . _The signal received by S1 is expressed as

in

and

are the channel responses from A ₁ to S ₁ and the receiver noise extracted by S ₁ , respectively, assuming that all channel responses are modeled as zero-mean complex Gaussian random variables (RVs), namely

in

and d is the distance between the transmitter and receiver, λ=c/f _c is the wavelength of the transmitted signal, c is the speed of light, and f _c is the carrier frequency of the transmitted signal. G _t and _Gr are transmit antenna gain and receive antenna gain, respectively. Assume that the receiver noise is also modeled as a zero-mean complex Gaussian random variable, such as

is hardware based. The received signal-to-noise ratio (Signal Noise Ratio, SNR) is expressed as

where P _t represents the transmission power.

给A₁，接收信号在A₁表示为

其中h_S1A1和

分别是S₁到A₁的信道响应和A₁的噪声，最后A₁计算双向ToA，

表示从挑战信号的最后一位发送到A₁响应信号完全解码的时间；

表示响应信号的最后一位到达A₁天线后直到响应信号被A₁完全解码的持续时间；

表示挑战信号的最后一位到达S₁天线后直到第一比特的响应信号从S₁天线发射的持续时间；t_tran表示传输时间。

和

是基于设备的，在定位过程中是常数，可以预先确定和预加载到A₁用于校准时间测量到一定的精度。t_tran＝2l/b，l是发射信号的长度和b为无线传感器网络的带宽。S ₁ sends a response signal

Given A ₁ , the received signal at A ₁ is represented as

where h _S1A1 and

are the channel response of S ₁ to A ₁ and the noise of A ₁ , respectively, and finally A ₁ calculates the bidirectional ToA,

Indicates the time from the transmission of the last bit of the challenge signal to the complete decoding _of the A1 response signal;

Indicates the duration from when the last bit _of the response signal reaches the A1 antenna until the response signal is fully decoded by A1 _;

Represents the duration of the last bit of the challenge signal reaching the S1 antenna until the _first bit of the response signal is transmitted from the S1 antenna; _{t tran} represents the transmission time.

and

is device-based, constant during positioning, and can be pre-determined and preloaded into A1 for calibrating time measurements to _a certain accuracy. t _tran = 2l/b, l is the length of the transmitted signal and b is the bandwidth of the wireless sensor network.

同样，其他的锚点也可以估计到的距离S₁。表示A_j和S_j的二维位置为

和

在不失一般性的前提下，假定第一个锚点A₁作为领导者从其他锚点收集所有定位信息。基于三个锚点的定位信息，A₁建立下列方程，

通过该方程，得到其位置为三个圆形成的交点，如图6所示。FIG. 6 is a schematic diagram of bidirectional positioning according to an embodiment of the present application. The estimated distance between A ₁ and S ₁ is

Similarly, other anchor points can also estimate the distance S ₁ . Representing the two-dimensional positions of A _j and S _j as

and

Without loss of generality, it is assumed that the _first anchor A1 acts as the leader to collect all positioning information from other anchors. Based on the positioning information of the _three anchor points, A1 establishes the following equation,

Through this equation, the position of the intersection formed by the three circles is obtained, as shown in Figure 6.

The positioning optimization method for a wireless sensor network provided in this embodiment has the following advantages: it can resist ranging attack according to the actual environment, and has strong flexibility; it has strong adaptability, because this solution ensures the security of sensor nodes under harsh conditions , such as the limited battery life of sensor nodes, the limited storage space of sensor nodes, and the high mobility of sensor nodes; no matter how many attacks are launched by external attackers, the security of the proposed scheme will not be affected.

In the wireless sensor positioning optimization solution provided by the embodiments of the present application, the first receiver noise extracted by the target node when receiving the challenge signal and the second receiver noise extracted by the anchor point when receiving the response signal are obtained; and the anchor point and The target distance of the target node; the target detection threshold is determined according to the upper limit of the false alarm probability; the detection result of the ranging attack is determined according to the noise of the first receiver, the noise of the second receiver and the target detection threshold; If the detection result of the increase attack is that there is no range increase attack, the target node is located according to the target distance; otherwise, the target distance is discarded. By adopting the above technical scheme, by extracting the receiver noise in the wireless transmission process, and according to the receiver noise and setting the upper limit of the false alarm probability, the detection of the range increase attack can be realized by one measurement. For sensor node positioning, since the upper limit of false alarm probability can be flexibly adjusted based on the actual situation, the flexibility of detection threshold is improved, communication overhead is saved on the basis of ensuring safe positioning, and the detection of range-increasing attacks is improved. flexibility.

的独立同分布指数随机变量，即

|X-Y|的概率密度函数(Probability Density Function，PDF)为

x＞0，|X-Y|的累积分布函数(Cumulative DistributionFunction，CDF)为

x＞0。证明过程可以根据相关技术进行证明，在此不进行说明。In some embodiments, the above Lemma 1 may be: If X and Y are parameters are

The independent and identically distributed exponential random variables of

The probability density function (PDF) of |XY| is

x>0, the cumulative distribution function (CDF) of |XY| is

x>0. The certification process can be certified according to related technologies, which will not be described here.

和

的独立分布指数型随机变量，即

和

In some embodiments, the above Lemma 2 may be: if X, Y and Z are with different parameters

and

independent distributed exponential random variable, that is

and

Then the PDF of |XYZ| is

The CDF of |XYZ| is

The certification process can be certified according to related technologies, which will not be described here.

FIG. 7 is a flowchart of another method for positioning optimization of a wireless sensor network according to an embodiment of the present application. This embodiment optimizes the above-mentioned positioning optimization method of the wireless sensor network on the basis of the above-mentioned embodiment. Correspondingly, the method of this embodiment includes:

S210: Acquire the first receiver noise extracted by the target node when receiving the challenge signal, and the second receiver noise extracted by the anchor point when receiving the response signal; and determine the target distance between the anchor point and the target node.

S220: Determine the target detection threshold according to the set false alarm probability upper limit value and the predetermined detection threshold expression.

In this embodiment, two situations are considered when determining the target detection threshold, one is a situation where there is a channel estimation error, and the other is a situation where there is no channel estimation error. That is, the target detection threshold includes detection thresholds in the presence of channel estimation errors and in the absence of channel estimation errors.

其中，P_fa表示误报概率，θ表示目标检测阈值，

表示响应信号或挑战信号的方差，

表示信道估计误差的方差。The detection threshold expression is:

Among them, P _fa represents the probability of false positives, θ represents the target detection threshold,

represents the variance of the response signal or challenge signal,

Represents the variance of the channel estimation error.

Determine whether the channel estimation error needs to be considered according to the current actual situation. When there is a channel estimation error, the upper limit of the false alarm probability can be set flexibly according to the actual situation, and the target detection threshold can also be changed flexibly, which improves the communication cost on the basis of saving. Flexibility; when there is no channel estimation error, the false alarm probability and target detection threshold are both zero.

Optionally, after determining the target detection threshold in this embodiment, the method may further include: determining the detection probability according to the target detection threshold, the false alarm probability expression and the detection probability expression, so as to verify the target detection threshold according to the detection probability.

After the detection probability is determined according to the target detection threshold, the false alarm probability expression and the detection probability expression, according to the detection probability and the optimal detection probability threshold, it can be verified that the performance of the current target detection threshold is better, that is, it is determined that the current environment is suitable for this implementation. method used in the example. The detection probability expression can be expressed as

S230. Determine the variance difference between the noise variance of the second receiver and the noise variance of the first receiver.

S240. Determine the detection result of the range-enhancing attack according to the comparison result between the variance difference and the target detection threshold.

According to the comparison result between the variance difference and the target detection threshold, determining the detection result of the range-enhancing attack may include: if the variance difference is less than or equal to the target detection threshold, the detection result of the range-enhancing attack is that there is no detection. Range augmentation attack; otherwise, the detection result of range augmentation attack is that range augmentation attack exists.

S250. Whether the detection result of the range increase attack is that there is no range increase attack, if so, execute S260; otherwise, execute S280.

S260. Whether the detection result of the ranging narrowing attack is that there is no ranging narrowing attack, if so, perform S270; otherwise, perform S280.

In this embodiment, the detection of the range reduction attack may be implemented in a manner in the related art, which is not limited here, and any methods that can detect the range reduction attack are applicable.

S270, locating the target node according to the target distance.

The two-way time-of-arrival algorithm can be used to locate the target node according to the target distance. The positioning method is as described above and will not be repeated here.

S280. Discard the target distance.

After discarding the target distance, the wireless sensor network can be checked for malicious nodes attacking to eliminate the attack, and the target node can be located until the attack detection result is that there is no ranging attack or ranging attack.

Next, the positioning optimization method of the wireless sensor network provided in this embodiment is verified through experimental simulation and analysis. This example studies the experimental results of the detection distance attack performance. These conclusions are also applicable to the performance evaluation of the security positioning scheme. There are two reasons for this. First, if all distance measurements are valid, then the final positioning result is also valid. ; Second, if the communication overhead in each distance measurement is low, the overall overhead of the secure localization scheme will also be low. For the setting of the number of sensor nodes, the experimental results for the simple case of four nodes, namely the number of anchors N _A =1, the number of target nodes N _S =1 and the number of malicious nodes N _E =2, are provided. When setting the positions of each sensor node, it is assumed that all anchor points and malicious nodes are distributed on the same plane, and the positions of four nodes are set first, as shown in FIG. 8 . FIG. Schematic diagram of a wireless sensor network system. Then let E ₁ move on a 30m×30m plane, set transmit power P _t =1W and transmit and receive antenna gains G _t =G _r =8.

In this embodiment, since both channel fading and receiver noise introduce randomness, in this embodiment, the final results of a set number of independent experimental schemes may be used for averaging, for example, the set number may be 60,000. In this embodiment, four performance indicators are taken as an example for description, and the first indicator is the probability of detection/probability of false alarm (PD/PFA). The second indicator is the Area Under Curve (AUC). According to the Neyman-Pearson (NP) theorem, the Receiver Operating Characteristic (ROC) curve is obtained, and then the corresponding ROC curve is calculated. the AUC. The third metric is communication overhead, defined as the total number of bits transmitted in one distance measurement. Due to the conflict between detection performance and overhead, various schemes are compared through the fourth indicator, Performance Overhead Ratio (POR), which is defined as the ratio of AUC to communication overhead.

An example is given by the comparison of the first indicator. Referring to FIG. 9, FIG. 9 is a schematic diagram comparing an experiment and a theory provided by an embodiment of the present application. The detection performance of this solution increases with the increase of the received noise _GE value of the malicious node. As shown in FIG. The noise ratio γ=10dB, the upper limit of false alarm probability ε=0.01, the performance of the adopted channel estimation algorithm α=5% and the hardware performance of malicious nodes β=100%. As shown in Figure 9, the closed-form expressions of PD and PFA are in perfect agreement with the expected simulation results. And, if the estimation error cannot be ignored, the detection performance of this scheme _improves as the value of GE increases. The value of _GE cannot be set too small by an external attacker, otherwise the signal received by the target node will be very low, and even the target node cannot decode the challenge signal, making distance attacks meaningless.

The detection performance of this scheme decreases with the increase of the value of α, where α represents the performance of the adopted channel estimation algorithm, and G _E =150 is set, and the other conditions are the same as those in FIG. 9 for analysis. As the value of β increases, the detection performance improves, β represents the hardware performance of the malicious node, and G _E = 150 is set, and the rest of the conditions are the same as in Figure 9 for analysis. When α and β increase in this scheme, the closed-form expressions of PD and PFA are in full agreement with the expected simulation results

As the distance between the target node and the malicious node decreases, the detection performance improves. Except for the position of G _E = 150 and E ₁ , the rest of the conditions are the same as those in Fig. 9 for analysis. However, if the estimation error cannot be ignored, the detection performance of this scheme improves as the distance between the target node and the malicious node decreases.

Next, this solution will be described by comparing the solution provided in this embodiment with the traditional solution. The detection performance of this solution has nothing to do with the number of measurements. As shown in FIG. 10 , FIG. 10 is a schematic diagram of the relationship between the detection performance and the number of measurements provided by an embodiment of the present application. The remaining conditions are the same as in FIG. 9 except that G _E =150 and M=3, and L represents the number of measurements in the conventional scheme. It can be seen from Figure 10 that the detection performance of this scheme is independent, while the detection performance of the traditional scheme increases with the increase of the value of L. When L≥2M+1, the detection performance of the traditional scheme is better, that is, AUC=1; otherwise, the detection performance of the traditional scheme is poor, that is, AUC is equal to 0.5, which is equivalent to random guessing. In the case of estimation error, the performance of the scheme decreases slightly, that is, AUC=0.992.

For different numbers of anchors, the proposed scheme can save 72.8% of the communication overhead compared with the traditional scheme, regardless of L. First, referring to FIG. 11 , FIG. 11 is a schematic diagram of a relationship between communication overhead and the number of anchor points provided by an embodiment of the present application, and other conditions are the same as those of FIG. 9 except that L=3. It can be seen from Fig. 11 that the communication overhead of this scheme and the traditional scheme both increase with the increase of the value of the number of anchor points NA _. But compared with the traditional scheme, this scheme has lower communication overhead. For example, if the IEEE 802.15.4 standard is adopted, for the case of 4 anchor points, the communication overhead of this scheme is 1.067Kbytes lower than that of the traditional scheme; for the case of 10 anchor points, the communication overhead of this scheme is 2.666Kbytes lower than that of the traditional scheme. For different numbers of anchors, compared with the traditional scheme, the communication overhead of this scheme is saved by 72.8%.

Next, referring to FIG. 12 , FIG. 12 is a schematic diagram of a relationship between communication overhead and the number of measurements provided by an embodiment of the present application, and other conditions are the same as those of FIG. 9 except that N _A =1. It can be seen from Figure 12 that as the number of measurements L increases, the communication overhead of the traditional scheme increases, while the communication overhead of this scheme is independent of L. Compared with the traditional scheme, this scheme has lower communication overhead, especially In the case of larger L. For example, when L=3, the communication overhead of this scheme is 0.267Kbytes lower than that of the original scheme; for L=10, the communication overhead of this scheme is 1.121Kbytes lower than that of the original scheme.

The POR value of this scheme is much better than that of the traditional scheme, and the POR value is independent of L. As shown in FIG. 13 , FIG. 13 is a schematic diagram of a relationship between a performance-overhead ratio and the number of measurements provided by an embodiment of the present application, where all conditions are the same as those in FIG. 10 . POR is defined as the ratio of AUC to communication overhead. It can be seen from Figure 13 that the POR value of this scheme is much better than that of the traditional scheme. The POR value of this scheme has nothing to do with L, while the POR value of the traditional scheme decreases with the increase of the L value, even if L≥2M+1. Figure 13 highlights the superiority of this scheme in terms of POR.

To sum up, in view of the security problem of node location when two malicious nodes cooperate to launch attacks in wireless sensor networks, this scheme uses the noise characteristics of external distance attacks to propose a lightweight security location scheme. Compared with the traditional scheme, this scheme provides lower communication overhead and higher security, and the experimental results show the superiority of this scheme.

In the wireless sensor positioning optimization solution provided by the embodiments of the present application, the first receiver noise extracted by the target node when receiving the challenge signal and the second receiver noise extracted by the anchor point when receiving the response signal are obtained; and the anchor point and The target distance of the target node; according to the upper limit value of the false alarm probability and the predetermined detection threshold expression, the target detection threshold is determined, and the variance difference between the noise variance of the second receiver and the noise variance of the first receiver is determined. According to the variance The comparison result of the difference value and the target detection threshold value determines the detection result of the ranging attack. If the detection result of the ranging attack is that there is no ranging attack, the detection result of the ranging attack is determined; If the detection result of the range reduction attack is that there is no range reduction attack, the target node is located according to the target distance. By adopting the above technical scheme, by extracting the receiver noise in the wireless transmission process, and according to the receiver noise and setting the upper limit of the false alarm probability, the detection of the range increase attack can be realized by one measurement. For sensor node positioning, since the upper limit of false alarm probability can be flexibly adjusted based on the actual situation, the flexibility of detection threshold is improved, communication overhead is saved on the basis of ensuring safe positioning, and the detection of range-increasing attacks is improved. flexibility.

FIG. 14 is a schematic structural diagram of an apparatus for positioning optimization of a wireless sensor network according to an embodiment of the present application. This embodiment is applicable to a situation in which secure positioning of a wireless sensor is implemented. The wireless sensor network positioning optimization apparatus provided by the embodiment of the present application can execute the wireless sensor network positioning optimization method provided by any embodiment of the present application, and has functional modules and effects corresponding to the execution method. The device includes:

The information acquisition module 310 is configured to acquire the first receiver noise extracted by the target node when receiving the challenge signal, and the second receiver noise extracted by the anchor point when receiving the response signal; and determine the anchor point and the target node The detection threshold determination module 320 is used to determine the target detection threshold according to the set false alarm probability upper limit value; the attack detection module 330 is used to determine the target detection threshold according to the first receiver noise, the second receiver noise and The target detection threshold is used to determine the detection result of the range increase attack; the positioning module 340 is configured to, if the detection result of the range increase attack is that there is no range increase attack, determine the target distance according to the target distance. The target node is positioned; otherwise, the target distance is discarded.

In the wireless sensor positioning optimization solution provided by the embodiments of the present application, the first receiver noise extracted by the target node when receiving the challenge signal and the second receiver noise extracted by the anchor point when receiving the response signal are obtained; and the anchor point and The target distance of the target node; the target detection threshold is determined according to the upper limit of the false alarm probability; the detection result of the ranging attack is determined according to the noise of the first receiver, the noise of the second receiver and the target detection threshold; If the detection result of the increase attack is that there is no range increase attack, the target node is located according to the target distance; otherwise, the target distance is discarded. By adopting the above technical scheme, by extracting the receiver noise in the wireless transmission process, and according to the receiver noise and setting the upper limit of the false alarm probability, the detection of the range increase attack can be realized by one measurement. For sensor node positioning, since the upper limit of false alarm probability can be flexibly adjusted based on the actual situation, the flexibility of detection threshold is improved, communication overhead is saved on the basis of ensuring safe positioning, and the detection of range-increasing attacks is improved. flexibility.

Optionally, the detection threshold determination module 320 is specifically configured to:

The target detection threshold is determined according to the set false alarm probability upper limit value and the predetermined detection threshold expression.

Optionally, the detection threshold expression is:

其中，P_fa表示误报概率，θ表示所述目标检测阈值，

表示所述响应信号或所述挑战信号的方差，

表示所述信道估计误差的方差。

Among them, P _fa represents the probability of false positives, θ represents the target detection threshold,

represents the variance of the response signal or the challenge signal,

represents the variance of the channel estimation error.

Optionally, the target detection threshold includes detection thresholds in the presence of the channel estimation error and the absence of the channel estimation error.

Optionally, the attack detection module 330 is used for:

Determine the variance difference between the noise variance of the second receiver and the noise variance of the first receiver; and determine the detection result of the ranging attack according to the comparison result of the variance difference and the target detection threshold.

Optionally, the attack detection module 330 is specifically used for:

If the variance difference is less than or equal to the target detection threshold, the detection result of the range augmentation attack is that the range increase attack does not exist; otherwise, the detection result of the range increase attack is the presence of the range increase attack. Range increases attack.

Optionally, the device further includes a ranging and narrowing attack module, which is specifically used for:

Before locating the target node according to the target distance, determine the detection result of the ranging attack; correspondingly, if the detection result of the ranging attack is that there is no ranging attack and the ranging attack When the detection result of the narrowing attack is that there is no ranging narrowing attack, the positioning of the target node according to the target distance is performed; otherwise, the target distance is discarded.

The wireless sensor network positioning optimization apparatus provided by the embodiment of the present application can execute the wireless sensor network positioning optimization method provided by any embodiment of the present application, and has functional modules and effects corresponding to the execution method.

FIG. 15 is a schematic structural diagram of a device provided by an embodiment of the present application. 15 shows a block diagram of an exemplary apparatus 412 suitable for use in implementing embodiments of the present application. The device 412 shown in FIG. 15 is only an example, and should not impose any limitations on the functions and scope of use of the embodiments of the present application.

As shown in FIG. 15, device 412 is represented as a generic device. Components of device 412 may include, but are not limited to, one or more processors 416, storage 428, and a bus 418 connecting various system components including storage 428 and processor 416.

Bus 418 represents one or more of several types of bus structures, including a storage device bus or storage device controller, a peripheral bus, a graphics acceleration port, a processor, or a local bus using any of a variety of bus structures. For example, these architectures include, but are not limited to, Industry Subversive Alliance (ISA) bus, Micro Channel Architecture (MAC) bus, enhanced ISA bus, Video Electronics Standards Association (Video Electronics Standards Association) , VESA) local bus and peripheral component interconnect (Peripheral Component Interconnect, PCI) bus.

Device 412 typically includes a variety of computer system readable media. These media can be any available media that can be accessed by device 412, including volatile and non-volatile media, removable and non-removable media.

Storage 428 may include computer system readable media in the form of volatile memory, such as random access memory (RAM) 430 and/or cache memory 432 . Device 412 may include other removable/non-removable, volatile/non-volatile computer system storage media. For example only, storage system 434 may be used to read and write to non-removable, non-volatile magnetic media (not shown in FIG. 15, commonly referred to as a "hard disk drive"). Although not shown in Figure 15, a magnetic disk drive may be provided for reading and writing to removable non-volatile magnetic disks (eg "floppy disks"), as well as removable non-volatile optical disks, such as Compact Disc Read -Only Memory, CD-ROM), digital video disc (Digital Video Disc-Read Only Memory, DVD-ROM) or other optical media) optical disc drive for reading and writing. In these cases, each drive may be connected to bus 418 through one or more data media interfaces. Storage 428 may include at least one program product having a set (eg, at least one) of program modules configured to perform the functions of various embodiments of the present application.

A program/utility 440 having a set (at least one) of program modules 442, which may be stored, for example, in storage device 428, such program modules 442 including, but not limited to, an operating system, one or more application programs, other program modules, and programs Data, each or some combination of these examples may include an implementation of a network environment. Program modules 442 generally perform the functions and/or methods of the embodiments described herein.

Device 412 may also communicate with one or more external devices 414 (eg, a keyboard, pointing terminal, display 424, etc.), may also communicate with one or more terminals that enable a user to interact with the device 412, and/or communicate with the device 412. Device 412 can communicate with any terminal (eg, network card, modem, etc.) that communicates with one or more other computing terminals. Such communication may take place through input/output (I/O) interface 422 . Also, device 412 may communicate with one or more networks (eg, Local Area Network (LAN), Wide Area Network (WAN), and/or public networks, such as the Internet) through network adapter 420 . As shown in FIG. 15 , network adapter 420 communicates with other modules of device 412 via bus 418 . It should be understood that, although not shown, other hardware and/or software modules may be used in conjunction with device 412, including but not limited to: microcode, terminal drivers, redundant processors, external disk drive arrays, Redundant Arrays of disks Independent Disks, RAID) systems, tape drives and data backup storage systems.

The processor 416 executes various functional applications and data processing by running the program stored in the storage device 428, for example, to realize the positioning optimization method of the wireless sensor network provided by the embodiment of the present application, the method includes: The first receiver noise extracted when challenging the signal, and the second receiver noise extracted by the anchor point when receiving the response signal; and determining the target distance between the anchor point and the target node; according to the upper limit of the false alarm probability value to determine the target detection threshold; according to the first receiver noise, the second receiver noise and the target detection threshold, determine the detection result of the ranging attack; if the detection result of the ranging attack is increased If there is no ranging attack, the target node is located according to the target distance; otherwise, the target distance is discarded.

Embodiments of the present application further provide a computer-readable storage medium, on which a computer program is stored, and when the program is executed by a processor, implements the positioning optimization method for a wireless sensor network as provided by the embodiments of the present application, and the method includes: Obtain the first receiver noise extracted by the target node when receiving the challenge signal, and the second receiver noise extracted by the anchor point when receiving the response signal; and determine the target distance between the anchor point and the target node; according to the setting The upper limit value of false alarm probability determines the target detection threshold; according to the first receiver noise, the second receiver noise and the target detection threshold, the detection result of the ranging increase attack is determined; if the ranging increase If the detection result of a large attack is that there is no ranging attack, the target node is located according to the target distance; otherwise, the target distance is discarded.

The computer storage medium of the embodiments of the present application may adopt any combination of one or more computer-readable media. The computer-readable medium may be a computer-readable signal medium or a computer-readable storage medium. The computer-readable storage medium can be, for example, but not limited to, an electrical, magnetic, optical, electromagnetic, infrared, or semiconductor system, apparatus or device, or a combination of any of the above. Examples (non-exhaustive list) of computer-readable storage media include: electrical connections with one or more wires, portable computer disks, hard disks, random access memory (RAM), read only memory (ROM), erasable Programmable read only memory (EPROM or flash memory), fiber optics, portable compact disk read only memory (CD-ROM), optical storage devices, magnetic storage devices, or any suitable combination of the above. In this document, a computer-readable storage medium can be any tangible medium that contains or stores a program that can be used by or in conjunction with an instruction execution system, apparatus, or device.

A computer-readable signal medium may include a propagated data signal in baseband or as part of a carrier wave, with computer-readable program code embodied thereon. Such propagated data signals may take a variety of forms, including but not limited to electromagnetic signals, optical signals, or any suitable combination of the foregoing. A computer-readable signal medium can also be any computer-readable medium other than a computer-readable storage medium that can transmit, propagate, or transport the program for use by or in connection with the instruction execution system, apparatus, or device .

Program code embodied on a computer readable medium may be transmitted using any suitable medium, including - but not limited to wireless, wireline, optical fiber cable, RF, etc., or any suitable combination of the foregoing.

Computer program code for performing the operations of the present application may be written in one or more programming languages, including object-oriented programming languages—such as Java, Smalltalk, C++, but also conventional Procedural programming language - such as the "C" language or similar programming language. The program code may execute entirely on the user's computer, partly on the user's computer, as a stand-alone software package, partly on the user's computer and partly on a remote computer, or entirely on the remote computer or terminal. In the case of a remote computer, the remote computer may be connected to the user's computer through any kind of network, including a local area network (LAN) or a wide area network (WAN), or may be connected to an external computer (eg, using an Internet service provider through Internet connection).

Claims (10)

1. A positioning optimization method of a wireless sensor network comprises the following steps:

acquiring first receiver noise extracted by a target node when receiving a challenge signal and second receiver noise extracted by an anchor point when receiving a response signal; determining the target distance between the anchor point and the target node;

determining a target detection threshold value according to a set upper limit value of the false alarm probability;

determining a detection result of the ranging increase attack according to the first receiver noise, the second receiver noise and the target detection threshold;

if the detection result of the ranging increase attack is that no ranging increase attack exists, positioning the target node according to the target distance; otherwise, the target distance is discarded.

2. The method of claim 1, wherein said determining a target detection threshold from a set false positive probability upper limit value comprises:

and determining a target detection threshold according to the set upper limit value of the false alarm probability and a predetermined detection threshold expression.

3. The method of claim 2, wherein the detection threshold expression is:

wherein, P_faTo representSetting a false alarm probability upper limit value, theta represents the target detection threshold value,

representing a variance of the response signal or the challenge signal,

representing the variance of the channel estimation error.

4. The method of claim 3, wherein the target detection threshold comprises a detection threshold for both the presence and absence of the channel estimation error.

5. The method of claim 1, wherein determining a detection result of a ranging increase attack based on the first receiver noise, the second receiver noise, and the target detection threshold comprises:

determining a variance difference of the second receiver noise variance and the first receiver noise variance;

and determining the detection result of the ranging increase attack according to the variance difference and the comparison result of the target detection threshold.

6. The method of claim 5, wherein determining the detection result of the ranging-up attack according to the comparison result of the variance difference and the target detection threshold comprises:

if the variance difference is smaller than or equal to the target detection threshold, the detection result of the ranging increase attack is that no ranging increase attack exists; otherwise, the detection result of the ranging increase attack is that the ranging increase attack exists.

7. The method of claim 1, further comprising, prior to locating the target node according to the target distance:

determining a detection result of the ranging reduction attack;

if the detection result of the ranging increase attack is that no ranging increase attack exists and the detection result of the ranging reduction attack is that no ranging reduction attack exists, the target node is positioned according to the target distance; otherwise, the target distance is discarded.

8. A positioning optimization apparatus for a wireless sensor network, comprising:

the information acquisition module is arranged to acquire first receiver noise extracted by the target node when receiving the challenge signal and second receiver noise extracted by the anchor point when receiving the response signal; determining the target distance between the anchor point and the target node;

the detection threshold value determining module is used for determining a target detection threshold value according to a set upper limit value of the false alarm probability;

the attack detection module is set to determine the detection result of the ranging augmentation attack according to the first receiver noise, the second receiver noise and the target detection threshold;

the positioning module is set to position the target node according to the target distance if the detection result of the ranging increase attack is that the ranging increase attack does not exist; otherwise, the target distance is discarded.

9. An apparatus, comprising:

one or more processors;

a storage device arranged to store one or more programs;

when executed by the one or more processors, cause the one or more processors to implement a method for location optimization for a wireless sensor network as recited in any of claims 1-7.

10. A computer-readable storage medium, in which a computer program is stored which, when being executed by a processor, carries out a method for location optimization of a wireless sensor network according to any one of claims 1 to 7.

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