Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on...Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on top of wireless networks.Unlike the traditional approaches focusing on developing jamming defense techniques without considering the location of jammers,we take a different viewpoint that the jammers'position should be identified and exploited for building a wide range of defense strategies to alleviate jamming.In this paper,we address the problem of localizing multiple jamming attackers coexisting in wireless networks by leveraging the network topology changes caused by jamming.We systematically analyze the jamming effects and develop a framework that can partition network topology into clusters and can successfully estimate the positions of multiple jammers even when their jamming areas are overlapping.Our experiments on a multi-hop network setup using MicaZ sensor nodes validate the feasibility of real-time collection of network topology changes under jamming and our extensive simulation results demonstrate that our approach is highly effective in localizing multiple attackers with or without the prior knowledge of the order that the jammers are turned on.展开更多
Jammers can awfully interfere with the wireless communications. The transmission and reception of wireless communication is blocked by the jammer. The intruder will place the jammer in a well topological network area ...Jammers can awfully interfere with the wireless communications. The transmission and reception of wireless communication is blocked by the jammer. The intruder will place the jammer in a well topological network area and they can easily track the information. It will help them to block the signal transmission and reception. Now, the intention is to track the position of the jammer where it is fixed. The existing methods rely on the indirect measurements and the boundary node to find the jammer’s position which degrades the accuracy of the localization. To improve the efficiency, this paper proposed an efficient method namely Coincered Node Based Localization of jammers to find the position of the jammer with high level of accuracy. The proposed system uses the direct measurements, which is the jammer signal strength. The effectiveness can also be increased by using the coincered node that will stumble across the true position of the jammer. The proposed work is compared with existing methods. Then the proposed mechanism proves better to find the jammer location. The simulation results estimate that the accuracy of the localization achieves better performance than the existing schemes.展开更多
In wireless sensor networks （WSNs）, as the shared nature of the wireless medium, jam- ming attacks can be easily launched and result in a great damage to the network. How to deal with jamming attacks has become a gr...In wireless sensor networks （WSNs）, as the shared nature of the wireless medium, jam- ming attacks can be easily launched and result in a great damage to the network. How to deal with jamming attacks has become a great concern recently. Finding the location of a jammer is important to take security actions against the jammer, and thus to restore the network communication. After a comprehensive study on the jammer localization problem, a lightweight easy-operated algorithm called triple circles localization （TCL） is proposed. The evaluation results have demonstrated that, compared with other approaches, TCL achieves the best jammer localization accuracy under variable conditions.展开更多
提出一种面向多跳无线网络的多干扰源定位算法,主要包括3个步骤:基于梯度下降法的分组投递率谷点推定、基于梯度上升法的接收干扰强度(RJSS,received jamming signal strength)峰点推定和聚类分析。首先,算法从多个初始节点出发,采用梯...提出一种面向多跳无线网络的多干扰源定位算法,主要包括3个步骤:基于梯度下降法的分组投递率谷点推定、基于梯度上升法的接收干扰强度(RJSS,received jamming signal strength)峰点推定和聚类分析。首先,算法从多个初始节点出发,采用梯度下降法,沿着分组投递率梯度下降最快的方向逼近干扰源,直至到达分组投递率谷点;然后应用功率自适应动态调整技术,采用梯度上升法,沿着接收干扰强度上升最快的方向继续逼近干扰源,直至接收干扰强度峰点(也称为RJSS停止节点);最后通过对无法与RJSS停止节点通信的邻居节点进行聚类分析,确定干扰源的数量和位置。模拟实验表明,与现有算法相比,所提算法可以有效降低多干扰源定位过程的定位误差;并且,当干扰源间距符合限定条件时,算法定位结果更优。展开更多
In wireless networks, jamming attacks are easy to launch and can significantly impact the network performance. The technique which localizes the jamming attacker is useful to address this problem. Some range-based loc...In wireless networks, jamming attacks are easy to launch and can significantly impact the network performance. The technique which localizes the jamming attacker is useful to address this problem. Some range-based localization schemes depend on the additional hardware of wireless nodes too much, and they can not work in resource-constrained wireless networks. Solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches.In this paper, we propose a novel range-free algorithm to localize the source of the attacker. We show that our approach only relies on the positions of each jammed or no-jammed node in the network, PSO algorithm is used to get the minimum covering circle of jammed positions and the circle center is the estimated jammer location. We compare our work with some existing range-free solutions via extensive simulations in two models, which are wireless sensor network (WSN) and vehicular ad hoc network (VANET) respectively. The experimental results suggest that our proposed algorithm achieves higher accuracy than the other solutions, and the localization error goes down with larger number of recorded jammed positions. In additional, when the recorded jammed positions are distributed in a specific constrained area, the localization error goes higher, we also propose an improved PSO algorithm to deal with this issue.展开更多
Localizing a jammer in an indoor environment in wireless sensor networks becomes a significant research problem due to the ease of blocking the communication between legitimate nodes. An adversary may emit radio frequ...Localizing a jammer in an indoor environment in wireless sensor networks becomes a significant research problem due to the ease of blocking the communication between legitimate nodes. An adversary may emit radio frequency to prevent the transmission between nodes. In this paper, we propose detecting the position of the jammer indoor by using the received signal strength and Kalman filter (KF) to reduce the noise due to the multipath signal caused by obstacles in the indoor environment. We compare our work to the Linear Prediction Algorithm (LP) and Centroid Localization Algorithm (CL). We observed that the Kalman filter has better results when estimating the distance compared to other algorithms.展开更多
基金partially supported by the National Natural Science Foundation of China under Grant No.62172080the Natural Science Foundation of Sichuan Province under Grants 2023NSFSC0478the National Key R&D Program of China No.2022YFB3103404
文摘Jamming attacks and unintentional radio interference are some of the most urgent threats harming the dependability of wireless communication and endangering the successful deployment of pervasive applications built on top of wireless networks.Unlike the traditional approaches focusing on developing jamming defense techniques without considering the location of jammers,we take a different viewpoint that the jammers'position should be identified and exploited for building a wide range of defense strategies to alleviate jamming.In this paper,we address the problem of localizing multiple jamming attackers coexisting in wireless networks by leveraging the network topology changes caused by jamming.We systematically analyze the jamming effects and develop a framework that can partition network topology into clusters and can successfully estimate the positions of multiple jammers even when their jamming areas are overlapping.Our experiments on a multi-hop network setup using MicaZ sensor nodes validate the feasibility of real-time collection of network topology changes under jamming and our extensive simulation results demonstrate that our approach is highly effective in localizing multiple attackers with or without the prior knowledge of the order that the jammers are turned on.
文摘Jammers can awfully interfere with the wireless communications. The transmission and reception of wireless communication is blocked by the jammer. The intruder will place the jammer in a well topological network area and they can easily track the information. It will help them to block the signal transmission and reception. Now, the intention is to track the position of the jammer where it is fixed. The existing methods rely on the indirect measurements and the boundary node to find the jammer’s position which degrades the accuracy of the localization. To improve the efficiency, this paper proposed an efficient method namely Coincered Node Based Localization of jammers to find the position of the jammer with high level of accuracy. The proposed system uses the direct measurements, which is the jammer signal strength. The effectiveness can also be increased by using the coincered node that will stumble across the true position of the jammer. The proposed work is compared with existing methods. Then the proposed mechanism proves better to find the jammer location. The simulation results estimate that the accuracy of the localization achieves better performance than the existing schemes.
文摘In wireless sensor networks （WSNs）, as the shared nature of the wireless medium, jam- ming attacks can be easily launched and result in a great damage to the network. How to deal with jamming attacks has become a great concern recently. Finding the location of a jammer is important to take security actions against the jammer, and thus to restore the network communication. After a comprehensive study on the jammer localization problem, a lightweight easy-operated algorithm called triple circles localization （TCL） is proposed. The evaluation results have demonstrated that, compared with other approaches, TCL achieves the best jammer localization accuracy under variable conditions.
文摘提出一种面向多跳无线网络的多干扰源定位算法,主要包括3个步骤:基于梯度下降法的分组投递率谷点推定、基于梯度上升法的接收干扰强度(RJSS,received jamming signal strength)峰点推定和聚类分析。首先,算法从多个初始节点出发,采用梯度下降法,沿着分组投递率梯度下降最快的方向逼近干扰源,直至到达分组投递率谷点;然后应用功率自适应动态调整技术,采用梯度上升法,沿着接收干扰强度上升最快的方向继续逼近干扰源,直至接收干扰强度峰点(也称为RJSS停止节点);最后通过对无法与RJSS停止节点通信的邻居节点进行聚类分析,确定干扰源的数量和位置。模拟实验表明,与现有算法相比,所提算法可以有效降低多干扰源定位过程的定位误差;并且,当干扰源间距符合限定条件时,算法定位结果更优。
文摘In wireless networks, jamming attacks are easy to launch and can significantly impact the network performance. The technique which localizes the jamming attacker is useful to address this problem. Some range-based localization schemes depend on the additional hardware of wireless nodes too much, and they can not work in resource-constrained wireless networks. Solutions in range-free localization are being pursued as a cost-effective alternative to more expensive range-based approaches.In this paper, we propose a novel range-free algorithm to localize the source of the attacker. We show that our approach only relies on the positions of each jammed or no-jammed node in the network, PSO algorithm is used to get the minimum covering circle of jammed positions and the circle center is the estimated jammer location. We compare our work with some existing range-free solutions via extensive simulations in two models, which are wireless sensor network (WSN) and vehicular ad hoc network (VANET) respectively. The experimental results suggest that our proposed algorithm achieves higher accuracy than the other solutions, and the localization error goes down with larger number of recorded jammed positions. In additional, when the recorded jammed positions are distributed in a specific constrained area, the localization error goes higher, we also propose an improved PSO algorithm to deal with this issue.
文摘Localizing a jammer in an indoor environment in wireless sensor networks becomes a significant research problem due to the ease of blocking the communication between legitimate nodes. An adversary may emit radio frequency to prevent the transmission between nodes. In this paper, we propose detecting the position of the jammer indoor by using the received signal strength and Kalman filter (KF) to reduce the noise due to the multipath signal caused by obstacles in the indoor environment. We compare our work to the Linear Prediction Algorithm (LP) and Centroid Localization Algorithm (CL). We observed that the Kalman filter has better results when estimating the distance compared to other algorithms.
