JOURNAL ARTICLE

Hardware Trojan Identification And Detection

Moein, SamerGebali, FayezT. Aaron GulliverAbdulrahman Alkandari

Year: 2017 Journal:   Zenodo (CERN European Organization for Nuclear Research)   Publisher: European Organization for Nuclear Research

Abstract

ABSTRACT The majority of techniques developed to detect hardware trojans are based on specific attributes. Further, the ad hoc approaches employed to design methods for trojan detection are largely ineffective. Hardware trojans have a number of attributes which can be used to systematically develop detection techniques. Based on this concept, a detailed examination of current trojan detection techniques and the characteristics of existing hardware trojans is presented. This is used to develop a new approach to hardware trojan identification and classification. This identification can be used to compare trojan risk or severity and trojan detection effectiveness. Identification vectors are generated for each hardware trojan and trojan detection technique based on the corresponding attributes. Vectors are also defined which represent trojan risk or severity and trojan detection effectiveness.

Keywords:
Trojan Hardware Trojan Identification (biology) Trojan horse

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Topics

Bioinformatics and Genomic Networks
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology
Radiomics and Machine Learning in Medical Imaging
Health Sciences →  Medicine →  Radiology, Nuclear Medicine and Imaging
Gene expression and cancer classification
Life Sciences →  Biochemistry, Genetics and Molecular Biology →  Molecular Biology

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