TY - GEN
T1 - Selective Concolic Testing for Hardware Trojan Detection in Behavioral SystemC Designs
AU - Lin, Bin
AU - Chen, Jinchao
AU - Xie, Fei
N1 - Publisher Copyright:
© 2020 EDAA.
PY - 2020/3
Y1 - 2020/3
N2 - With the growing complexities of modern SoC designs and increasingly shortened time-to-market requirements, new design paradigms such as outsourced design services have emerged. Design abstraction level has also been raised from RTL to ESL. Modern SoC designs in ESL often integrate a variety of third-party behavioral intellectual properties, as well as intensively utilizing EDA tools to improve design productivity. However, this new design trend makes modern SoCs more vulnerable to hardware Trojan attacks. Although hardware Trojan detection has been studied for more than a decade in RTL and lower levels, it has only recently gained attention in ESL designs. In this paper, we present a novel approach for generating test cases by selective concolic testing to detect hardware Trojans in ESL. We have evaluated our approach on an open source benchmark that includes various types of hardware Trojans. The experimental results demonstrate that our approach is able to detect hardware Trojans effectively and efficiently.
AB - With the growing complexities of modern SoC designs and increasingly shortened time-to-market requirements, new design paradigms such as outsourced design services have emerged. Design abstraction level has also been raised from RTL to ESL. Modern SoC designs in ESL often integrate a variety of third-party behavioral intellectual properties, as well as intensively utilizing EDA tools to improve design productivity. However, this new design trend makes modern SoCs more vulnerable to hardware Trojan attacks. Although hardware Trojan detection has been studied for more than a decade in RTL and lower levels, it has only recently gained attention in ESL designs. In this paper, we present a novel approach for generating test cases by selective concolic testing to detect hardware Trojans in ESL. We have evaluated our approach on an open source benchmark that includes various types of hardware Trojans. The experimental results demonstrate that our approach is able to detect hardware Trojans effectively and efficiently.
UR - http://www.scopus.com/inward/record.url?scp=85087393275&partnerID=8YFLogxK
U2 - 10.23919/DATE48585.2020.9116384
DO - 10.23919/DATE48585.2020.9116384
M3 - 会议稿件
AN - SCOPUS:85087393275
T3 - Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
SP - 19
EP - 24
BT - Proceedings of the 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
A2 - Di Natale, Giorgio
A2 - Bolchini, Cristiana
A2 - Vatajelu, Elena-Ioana
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2020 Design, Automation and Test in Europe Conference and Exhibition, DATE 2020
Y2 - 9 March 2020 through 13 March 2020
ER -