{"title":"保护ISAC免受飞行员欺骗攻击:一种深度即插即用对策","authors":"Guo Li;Chao Wang;Haibin Zhang;Liang Jin;Naofal Al-Dhahir","doi":"10.1109/LWC.2025.3580067","DOIUrl":null,"url":null,"abstract":"In this letter, we propose a deep plug-and-play prior approach for designing a robust integrated sensing and communication (ISAC) precoder that combats the pilot spoofing attack for the first time. Specifically, our precoder design is formulated as a robust optimization problem that maximizes the sensing power while minimizing the eavesdropping signal-to-interference-plus-noise ratio simultaneously, even without the need for knowledge of the victim’s and eavesdropper’s channel state information. To address this challenging design problem, a deep learning network is exploited to minimize the information leakage, which is subsequently integrated and plugged in as a modular component into an iterative precoder optimization algorithm, under a communication constraint. Simulation results confirm the secrecy performance of our proposed deep prior induced ISAC precoder design approach.","PeriodicalId":13343,"journal":{"name":"IEEE Wireless Communications Letters","volume":"14 9","pages":"2813-2817"},"PeriodicalIF":5.5000,"publicationDate":"2025-06-16","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Securing ISAC Against Pilot Spoofing Attack: A Deep Plug-and-Play Countermeasure\",\"authors\":\"Guo Li;Chao Wang;Haibin Zhang;Liang Jin;Naofal Al-Dhahir\",\"doi\":\"10.1109/LWC.2025.3580067\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"In this letter, we propose a deep plug-and-play prior approach for designing a robust integrated sensing and communication (ISAC) precoder that combats the pilot spoofing attack for the first time. Specifically, our precoder design is formulated as a robust optimization problem that maximizes the sensing power while minimizing the eavesdropping signal-to-interference-plus-noise ratio simultaneously, even without the need for knowledge of the victim’s and eavesdropper’s channel state information. To address this challenging design problem, a deep learning network is exploited to minimize the information leakage, which is subsequently integrated and plugged in as a modular component into an iterative precoder optimization algorithm, under a communication constraint. Simulation results confirm the secrecy performance of our proposed deep prior induced ISAC precoder design approach.\",\"PeriodicalId\":13343,\"journal\":{\"name\":\"IEEE Wireless Communications Letters\",\"volume\":\"14 9\",\"pages\":\"2813-2817\"},\"PeriodicalIF\":5.5000,\"publicationDate\":\"2025-06-16\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"IEEE Wireless Communications Letters\",\"FirstCategoryId\":\"94\",\"ListUrlMain\":\"https://ieeexplore.ieee.org/document/11037496/\",\"RegionNum\":3,\"RegionCategory\":\"计算机科学\",\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"COMPUTER SCIENCE, INFORMATION SYSTEMS\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"IEEE Wireless Communications Letters","FirstCategoryId":"94","ListUrlMain":"https://ieeexplore.ieee.org/document/11037496/","RegionNum":3,"RegionCategory":"计算机科学","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"COMPUTER SCIENCE, INFORMATION SYSTEMS","Score":null,"Total":0}
Securing ISAC Against Pilot Spoofing Attack: A Deep Plug-and-Play Countermeasure
In this letter, we propose a deep plug-and-play prior approach for designing a robust integrated sensing and communication (ISAC) precoder that combats the pilot spoofing attack for the first time. Specifically, our precoder design is formulated as a robust optimization problem that maximizes the sensing power while minimizing the eavesdropping signal-to-interference-plus-noise ratio simultaneously, even without the need for knowledge of the victim’s and eavesdropper’s channel state information. To address this challenging design problem, a deep learning network is exploited to minimize the information leakage, which is subsequently integrated and plugged in as a modular component into an iterative precoder optimization algorithm, under a communication constraint. Simulation results confirm the secrecy performance of our proposed deep prior induced ISAC precoder design approach.
期刊介绍:
IEEE Wireless Communications Letters publishes short papers in a rapid publication cycle on advances in the state-of-the-art of wireless communications. Both theoretical contributions (including new techniques, concepts, and analyses) and practical contributions (including system experiments and prototypes, and new applications) are encouraged. This journal focuses on the physical layer and the link layer of wireless communication systems.