Visible to the public Detection and Masking of Trojan Circuits in Sequential Logic

TitleDetection and Masking of Trojan Circuits in Sequential Logic
Publication TypeConference Paper
Year of Publication2017
AuthorsMatrosova, A., Mitrofanov, E., Ostanin, S., Nikolaeva, E.
Conference Name2017 IEEE East-West Design Test Symposium (EWDTS)
ISBN Number978-1-5386-3299-4
Keywordsbinary decision diagrams, Boolean functions, composability, Controllability, cyber physical systems, Estimation, graph theory, internal node controllability, internal node observability, Logic gates, Observability, precise random estimations, pubcrawl, reduced ordered binary decision diagrams, resilience, Resiliency, ROBDDs, sequential circuit nodes, sequential circuits, state estimation, state transition graph description, state variables, STG description, sub-circuit overhead masking, TC switch, TC switch description, Trojan circuit detection, Trojan circuit masking, trojan horse detection, Trojan horses
Abstract

A technique of finding a set of sequential circuit nodes in which Trojan Circuits (TC) may be implanted is suggested. The technique is based on applying the precise (not heuristic) random estimations of internal node observability and controllability. Getting the estimations we at the same time derive and compactly represent all sequential circuit full states (depending on input and state variables) in which of that TC may be switched on. It means we obtain precise description of TC switch on area for the corresponding internal node v. The estimations are computed with applying a State Transition Graph (STG) description, if we suppose that TC may be inserted out of the working area (out of the specification) of the sequential circuit. Reduced Ordered Binary Decision Diagrams (ROBDDs) for the combinational part and its fragments are applied for getting the estimations by means of operations on ROBDDs. Techniques of masking TCs are proposed. Masking sub-circuits overhead is appreciated.

URLhttps://ieeexplore.ieee.org/document/8110101/
DOI10.1109/EWDTS.2017.8110101
Citation Keymatrosova_detection_2017