Trojan Detection via Side-Channel Sensitivity Maximization
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Solution Overview
Problem
Existing Trojan detection techniques face challenges in scalability and sensitivity due to exponential test generation time and marginal side-channel sensitivity compared to noise and process variations, especially in large System-on-Chip (SoC) designs.
Innovation Solution
An efficient test generation technique using a genetic algorithm to maximize side-channel sensitivity by exploiting input affinity and minimizing switching in non-suspicious regions, targeting dynamic current as a side-channel signature, which can be extended to other parameters with suitable modifications.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If existing Trojan detection techniques are applied to large SoC designs, then Trojan detection capability is provided, but test generation time grows exponentially and side-channel sensitivity is marginal compared to noise and process variations
Solution Approach 1:
The patent segments the test generation process by identifying and focusing only on suspicious regions within the circuit design. Instead of generating tests for the entire large SoC design, the method divides the circuit into suspicious and non-suspicious regions, and generates tests specifically targeted at the suspicious regions. This segmentation dramatically reduces test generation time while maintaining detection effectiveness.
Solution Approach 2:
The patent applies local quality by making different parts of the circuit undergo different treatment. Suspicious regions are subjected to detailed side-channel analysis and targeted test generation, while non-suspicious regions are excluded or minimized in the test generation process. This localized approach concentrates computational resources where they are most needed, improving both sensitivity and efficiency.
2Reliability
If comprehensive test patterns are generated to detect Trojans, then detection coverage is improved, but test generation complexity and time increase exponentially
Solution Approach 1:
The patent performs preliminary action by pre-identifying suspicious regions in the circuit design before test generation. Using static analysis and heuristic methods, the system预先 marks regions that are likely to contain Trojans based on design patterns, insertion points, and risk assessment. This preliminary identification allows subsequent test generation to focus only on these marked regions, dramatically reducing complexity while maintaining detection coverage.
Solution Approach 2:
The patent applies partial action by generating test patterns that are sufficient to detect Trojans in suspicious regions without requiring exhaustive coverage of the entire circuit. The method generates enough test patterns to achieve high detection probability in targeted regions, rather than attempting complete coverage of all circuit paths, which would be computationally infeasible for large designs.
3Measurement precision
If side-channel analysis is used for Trojan detection, then non-intrusive detection is achieved, but sensitivity is marginal compared to noise and process variations
Solution Approach 1:
The patent applies parameter changes by dynamically adjusting test conditions and measurement parameters to maximize the signal from potential Trojans. The system varies input patterns, measurement timing, and analysis parameters to enhance the side-channel signatures from suspicious regions while minimizing the impact of noise and process variations. This adaptive parameter adjustment significantly improves detection sensitivity.
Solution Approach 2:
The patent uses copying by creating multiple copies of test patterns and applying them in sequence to the suspicious regions. By repeatedly applying similar test patterns with slight variations and aggregating the results, the system amplifies the signal from potential Trojans while averaging out random noise. This repeated measurement approach enhances sensitivity without requiring more invasive detection methods.
Data Source
AI summary
An exemplary method of detecting a Trojan circuit in an integrated circuit is related to applying a test pattern comprising an initial test pattern followed by a corresponding succeeding test pattern to a golden design of the integrated circuit, wherein a change in the test pattern increases side-channel sensitivity; measuring a side-channel parameter in the golden design of the integrated circuit after application of the test pattern; applying the test pattern to a design of the integrated circuit under test; measuring the side-channel parameter in the design of the integrated circuit under test after application of the test pattern; and determining a Trojan circuit to be present in the integrated circuit under test when the measured side-channel parameters vary by a threshold.


