Hardware Trojan horse detection method based on low activity and low observation node conjoint analysis

The hardware Trojan detection method, which combines low-activity and low-observation-node analysis, solves the problems of insufficient detection coverage and high computational overhead in existing technologies. It achieves efficient and accurate detection and localization of highly concealed hardware Trojans and is suitable for large-scale integrated circuit design.

CN122389102APending Publication Date: 2026-07-14TIANJIN UNIV
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Patent Information

Application Number
CN202610736686.3
Authority / Receiving Office
CN · China
Patent Type
Applications(China)
Current Assignee / Owner
Filing Date
2026-05-26
Publication Date
2026-07-14

AI Technical Summary

Technical Problem

Existing technologies struggle to efficiently and accurately identify and locate hardware Trojans that employ low-activity triggering and low-observation-output strategies for double concealment, resulting in insufficient detection coverage, low signal-to-noise ratio, high computational overhead, or poor scalability.

Method used

A hardware Trojan detection method based on joint analysis of low-activity and low-observation nodes is adopted, including dynamic functional simulation, testability analysis and signal propagation path search. A set of low-activity candidate trigger nodes and a set of low-observation candidate payload nodes are constructed. Path mining is carried out in combination with the directed graph of signal propagation to identify potential links of high-risk hardware Trojans.

Benefits of technology

It significantly improves the detection accuracy and coverage of highly stealthy hardware Trojans, reduces computational overhead, and realizes the automation and scalability of the detection process, making it suitable for large-scale integrated circuit design.

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Abstract

The invention discloses a hardware Trojan horse detection method and system based on low activity and low observation node conjoint analysis, belongs to the technical field of integrated circuit safety, and solves the problem of how to improve the accuracy of identifying high-concealment hardware Trojan horses. Abstracting the gate-level netlist into a signal propagation directed graph, searching an effective signal propagation path from a starting node to a target node in the directed graph by taking the node in the low-activity candidate trigger node set as the starting node and taking the node in the low-observability candidate load node set as the target node, and if the effective signal propagation path exists, executing the next step; if so, determining that the link is a high-risk hardware Trojan potential link; the method for identifying the high-concealment hardware Trojan horse potential signal link through static analysis based on the gate-level netlist does not depend on a golden reference model, does not need a known Trojan horse feature library, and is particularly suitable for scenes such as third-party IP approval security detection, backdoor review and logic credibility verification.
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