TY - GEN
T1 - Advanced techniques for designing stealthy hardware trojans
AU - Tsoutsos, Nektarios Georgios
AU - Konstantinou, Charalambos
AU - Maniatakos, Michail
N1 - Generated from Scopus record by KAUST IRTS on 2022-09-13
PY - 2014/1/1
Y1 - 2014/1/1
N2 - The necessity of detecting malicious modications in hard-ware designs has led to the development of various detec-tion tools. Trojan detection approaches aim to reveal com-promised designs using several methods such as static code analysis, side-channel dynamic signal analysis, design for testing, verication, and monitoring architectures etc. This paper demonstrates new approaches for circumventing some of the latest Trojan detection techniques. We introduce and implement stealthy Trojans designs that do not violate the functional specications of the corresponding original mod-els. The designs chosen to demonstrate the effectiveness of our techniques correspond to encryption algorithms and a pseudo random number generator. The proposed Trojans are inserted into the original RTL, and decrease the overall security of the designs, minimizing detection probability by state-of-the-art static analysis tools. Copyright 2014 ACM.
AB - The necessity of detecting malicious modications in hard-ware designs has led to the development of various detec-tion tools. Trojan detection approaches aim to reveal com-promised designs using several methods such as static code analysis, side-channel dynamic signal analysis, design for testing, verication, and monitoring architectures etc. This paper demonstrates new approaches for circumventing some of the latest Trojan detection techniques. We introduce and implement stealthy Trojans designs that do not violate the functional specications of the corresponding original mod-els. The designs chosen to demonstrate the effectiveness of our techniques correspond to encryption algorithms and a pseudo random number generator. The proposed Trojans are inserted into the original RTL, and decrease the overall security of the designs, minimizing detection probability by state-of-the-art static analysis tools. Copyright 2014 ACM.
UR - http://dl.acm.org/citation.cfm?doid=2593069.2596668
UR - http://www.scopus.com/inward/record.url?scp=84903164661&partnerID=8YFLogxK
U2 - 10.1145/2593069.2596668
DO - 10.1145/2593069.2596668
M3 - Conference contribution
SN - 9781479930173
BT - Proceedings - Design Automation Conference
PB - Institute of Electrical and Electronics Engineers Inc.
ER -