Jointly beam stealing attackers detection and localization without training:an image processing viewpoint  

作　　者：Yaoqi YANG Xianglin WEI Renhui XU Weizheng WANG Laixian PENG Yangang WANG 

机构地区：[1]College of Communication Engineer,Army Engineering University of PLA,Nanjing 210000,China [2]The 63rd Research Institute,National University of Defense Technology,Nanjing 210007,China [3]Department of Computer Science,City University of Hong Kong,Hong Kong 999077,China

出　　处：《Frontiers of Computer Science》2023年第3期145-160,共16页中国计算机科学前沿（英文版）

基　　金：This work was supported in part by the National Natural Science Foundation of China(Grant No.61671471)。

摘　　要：Recently revealed beam stealing attacks could greatly threaten the security and privacy of IEEE 802.11ad communications.The premise to restore normal network service is detecting and locating beam stealing attackers without their cooperation.Current consistency-based methods are only valid for one single attacker and are parametersensitive.From the viewpoint of image processing,this paper proposes an algorithm to jointly detect and locate multiple beam stealing attackers based on RSSI(Received Signal Strength Indicator)map without the training process involved in deep learning-based solutions.Firstly,an RSSI map is constructed based on interpolating the raw RSSI data for enabling high-resolution localization while reducing monitoring cost.Secondly,three image processing steps,including edge detection and segmentation,are conducted on the constructed RSSI map to detect and locate multiple attackers without any prior knowledge about the attackers.To evaluate our proposal’s performance,a series of experiments are conducted based on the collected data.Experimental results have shown that in typical parameter settings,our algorithm’s positioning error does not exceed 0.41 m with a detection rate no less than 91%.

关 键 词：beam-stealing attacks DETECTION LOCALIZATION image processing 

分 类 号：TN91[电子电信—通信与信息系统]