A. Darjani, N. Kavand, Shubham Rai, M. Wijtvliet, Akash Kumar
{"title":"ENTANGLE: An Enhanced Logic-locking Technique for Thwarting SAT and Structural Attacks","authors":"A. Darjani, N. Kavand, Shubham Rai, M. Wijtvliet, Akash Kumar","doi":"10.1145/3526241.3530371","DOIUrl":null,"url":null,"abstract":"Among the SAT-resilient logic locking techniques, the Stripped-Functionality-Logic-Locking (SFLL) is the most promising solution which can guard the intellectual property against approximate, sensitization, SAT, and structural attacks which target Point-function techniques. However, even the SFLL technique has been shown to be vulnerable to a recent class of structural attacks that identify the perturbation logic. In this paper, we first categorize all possible classes of attacks on SFLL. Then we propose ENTANGLE a novel logic locking technique built upon SFLL that can resist all of these attacks, including the emerging ML-Based attacks. We test our technique against publicly available SFLL attacks. The implementation results show that ENTANGLE can secure large-sized industrial circuits with an average overhead of 11.6 percent and 9.1 percent for area and power, respectively.","PeriodicalId":188228,"journal":{"name":"Proceedings of the Great Lakes Symposium on VLSI 2022","volume":"37 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2022-06-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Proceedings of the Great Lakes Symposium on VLSI 2022","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1145/3526241.3530371","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
Among the SAT-resilient logic locking techniques, the Stripped-Functionality-Logic-Locking (SFLL) is the most promising solution which can guard the intellectual property against approximate, sensitization, SAT, and structural attacks which target Point-function techniques. However, even the SFLL technique has been shown to be vulnerable to a recent class of structural attacks that identify the perturbation logic. In this paper, we first categorize all possible classes of attacks on SFLL. Then we propose ENTANGLE a novel logic locking technique built upon SFLL that can resist all of these attacks, including the emerging ML-Based attacks. We test our technique against publicly available SFLL attacks. The implementation results show that ENTANGLE can secure large-sized industrial circuits with an average overhead of 11.6 percent and 9.1 percent for area and power, respectively.