{"title":"On the Effect of Aging in Detecting Hardware Trojan Horses with Template Analysis","authors":"Naghmeh Karimi, J. Danger, S. Guilley","doi":"10.1109/IOLTS.2018.8474089","DOIUrl":null,"url":null,"abstract":"With the outsourcing of design flow, ensuring the security and trustworthiness of integrated circuits has become more challenging. Potential malicious modification of circuits, so-called Hardware Trojans Horses (HTH), has emerged as a major security threat. When triggered, the HTH delivers its payload resulting in denial of service, decreasing the device performance, or leaking sensitive information. Deploying VLSI testing schemes to detect HTH may fail in most cases as HTH are designed such that they are rarely activated. Side-channel analysis schemes have a higher detection coverage. The template analysis is the most powerful side-channel tool from an information theoretic point of view. In this paper, we focus on the template analysis used for detecting HTH in cryptographic devices, and study the effect of device aging on the success of these HTH detection schemes. Due to aging, electrical specifications of transistors, and in turn the power signatures used by template schemes change over time. We focus on Negative-Bias Temperature Instability and Hot-Carrier Injection aging mechanisms. We use the PRESENT cipher as a target, and mount several template attacks at different aging times on target devices and a genuine device used as reference. We deduce the authenticity of the target devices based on the attack success rates obtained by template analysis. Our results show that aging makes template-based HTH detection easier as it needs less traces in old devices compared to the new one (137 traces for a 20-week old device versus 195 traces for a new one).","PeriodicalId":241735,"journal":{"name":"2018 IEEE 24th International Symposium on On-Line Testing And Robust System Design (IOLTS)","volume":"31 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"6","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2018 IEEE 24th International Symposium on On-Line Testing And Robust System Design (IOLTS)","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/IOLTS.2018.8474089","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 6
Abstract
With the outsourcing of design flow, ensuring the security and trustworthiness of integrated circuits has become more challenging. Potential malicious modification of circuits, so-called Hardware Trojans Horses (HTH), has emerged as a major security threat. When triggered, the HTH delivers its payload resulting in denial of service, decreasing the device performance, or leaking sensitive information. Deploying VLSI testing schemes to detect HTH may fail in most cases as HTH are designed such that they are rarely activated. Side-channel analysis schemes have a higher detection coverage. The template analysis is the most powerful side-channel tool from an information theoretic point of view. In this paper, we focus on the template analysis used for detecting HTH in cryptographic devices, and study the effect of device aging on the success of these HTH detection schemes. Due to aging, electrical specifications of transistors, and in turn the power signatures used by template schemes change over time. We focus on Negative-Bias Temperature Instability and Hot-Carrier Injection aging mechanisms. We use the PRESENT cipher as a target, and mount several template attacks at different aging times on target devices and a genuine device used as reference. We deduce the authenticity of the target devices based on the attack success rates obtained by template analysis. Our results show that aging makes template-based HTH detection easier as it needs less traces in old devices compared to the new one (137 traces for a 20-week old device versus 195 traces for a new one).