TY - GEN
T1 - Detecting the Existence of Malfunctions in Microcontrollers Utilizing Power Analysis
AU - Hasegawa, Kento
AU - Yanagisawa, Masao
AU - Togawa, Nozomu
N1 - Publisher Copyright:
© 2018 IEEE.
PY - 2018/9/26
Y1 - 2018/9/26
N2 - 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.
AB - 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.
KW - hardware security
KW - malfunction
KW - microcontroller
KW - power analysis
KW - sleep mode
UR - http://www.scopus.com/inward/record.url?scp=85055835202&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85055835202&partnerID=8YFLogxK
U2 - 10.1109/IOLTS.2018.8474113
DO - 10.1109/IOLTS.2018.8474113
M3 - Conference contribution
AN - SCOPUS:85055835202
T3 - 2018 IEEE 24th International Symposium on On-Line Testing and Robust System Design, IOLTS 2018
SP - 97
EP - 102
BT - 2018 IEEE 24th International Symposium on On-Line Testing and Robust System Design, IOLTS 2018
A2 - Maniatakos, Mihalis
A2 - Alexandrescu, Dan
A2 - Gizopoulos, Dimitris
A2 - Papavramidou, Panagiota
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 24th IEEE International Symposium on On-Line Testing and Robust System Design, IOLTS 2018
Y2 - 2 July 2018 through 4 July 2018
ER -