摘要
The increasing reliance on third-party intellectual property (IP) cores in modern integrated circuit (IC) design has introduced significant security vulnerabilities, particularly the risk of Hardware Trojans (HTs). These malicious modifications can compromise system integrity, leading to data leakage, unauthorized access, or functional failures. Traditional detection methods often depend on the availability of a golden chip, which is not always feasible. This paper presents the 2025 ICCAD CAD Contest Problem A, which challenges participants to develop machine learning-based solutions for detecting HTs directly from gate-level netlists without requiring a golden reference. The problem is formulated with defined Trojan behaviors, input/output specifications, and evaluation metrics, including correctness and F1 score. The contest aims to foster innovation in HT detection by leveraging advanced data-driven techniques and scalable analysis frameworks.