Conventional and machine learning approaches as countermeasures against hardware trojan attacks

作     者：Liakos, Konstantinos G. Georgakilas, Georgios K. Moustakidis, Serafeim Sklavos, Nicolas Plessas, Fotis C. 

作者机构：Univ Thessaly Sch Engn Dept Elect & Comp Engn CAS Lab Grp Volos Hellas Greece AIDEAS Tallinn Estonia Univ Patras Dept Comp Engn & Informat Patras Hellas Greece 

出 版 物：《MICROPROCESSORS AND MICROSYSTEMS》 (微处理机与微型系统)

年 卷 期：2020年第79卷

页      面：103295-103295页

核心收录：

学科分类：0808[工学-电气工程] 08[工学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

基　　金：European Commission  EC 

主　　题：Hardware security Hardware trojans Integrated circuits Application-specific integrated circuit Field-programmable gate array Artificial intelligence Machine learning Detection Prevention Facilitation Design for security Runtime monitor Literature review 

摘      要：Every year, the rate at which technology is applied on areas of our everyday life is increasing at a steady pace. This rapid development drives the technology companies to design and fabricate their integrated circuits (ICs) in non-trustworthy outsourcing foundries to reduce the cost, thus, leaving space for a synchronous form of virus, known as Hardware Trojan (HT), to be developed. HTs leak encrypted information, degrade device performance or lead to total destruction. To reduce the risks associated with these viruses, various approaches have been developed aiming to prevent and detect them, based on conventional or machine learning methods. Ideally, any undesired modification made to an IC should be detectable by pre-silicon verification/simulation and post-silicon testing. The infected circuit can be inserted in different stages of the manufacturing process, rendering the detection of HTs a complicated procedure. In this paper, we present a comprehensive review of research dedicated to countermeasures against HTs embedded into ICs. The literature is grouped in four main categories;(a) conventional HT detection approaches, (b) machine learning for HT countermeasures, (c) design for security and (d) runtime monitor.