{"title":"Detecting the Existence of Malfunctions in Microcontrollers Utilizing Power Analysis","authors":"Kento Hasegawa, M. Yanagisawa, N. Togawa","doi":"10.1109/IOLTS.2018.8474113","DOIUrl":null,"url":null,"abstract":"Microcontrollers are widely used in electric devices such as smart phones, televisions, and other smart IoT (Internet-of-Things) devices. Because of the increase of these smart IoT devices, the security of hardware devices becomes a serious concern. In this paper, we propose a method which detects the existence of malfunctions implemented in microcontrollers utilizing power analysis. Our method firstly measures power consumption of the target device and classifies its waveform into the sleep-mode part, in which a microcontroller saves power, and the active-mode part, in which a microcontroller works in a normal operation. After that, we focus on the active-mode part and extract several features from the waveform, which effectively distinguish between normal operations and malfunctions. Finally, we classify the features and identify whether malfunctions exist or not. Our experimental results demonstrate that our proposed method successfully detects the existence of malfunctions in our benchmark.","PeriodicalId":241735,"journal":{"name":"2018 IEEE 24th International Symposium on On-Line Testing And Robust System Design (IOLTS)","volume":"52 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2018-07-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"3","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.2018.8474113","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 3
Abstract
Microcontrollers are widely used in electric devices such as smart phones, televisions, and other smart IoT (Internet-of-Things) devices. Because of the increase of these smart IoT devices, the security of hardware devices becomes a serious concern. In this paper, we propose a method which detects the existence of malfunctions implemented in microcontrollers utilizing power analysis. Our method firstly measures power consumption of the target device and classifies its waveform into the sleep-mode part, in which a microcontroller saves power, and the active-mode part, in which a microcontroller works in a normal operation. After that, we focus on the active-mode part and extract several features from the waveform, which effectively distinguish between normal operations and malfunctions. Finally, we classify the features and identify whether malfunctions exist or not. Our experimental results demonstrate that our proposed method successfully detects the existence of malfunctions in our benchmark.