2024/03/19 by Raghul Saravanan, Saravanan, Raghul, Sai Manoj Pudukotai Dinakarrao +1 · 1 citation
Engineering · #Cryptography and Security (cs.CR) #FOS: Computer and information sciences #Modular Robots and Swarm Intelligence
paper · pdf · doi:10.48550/arxiv.2403.12812
openalex publication_date 2024/03/19 · openalex created_date 2025/10/10 · openalex updated_date 2026/07/28
In recent years, there has been a notable surge in attention towards hardware security, driven by the increasing complexity and integration of processors, SoCs, and third-party IPs aimed at delivering advanced solutions. However, this complexity also introduces vulnerabilities and bugs into hardware systems, necessitating early detection during the IC design cycle to uphold system integrity and mitigate re-engineering costs. While the Design Verification (DV) community employs dynamic and formal verification strategies, they encounter challenges such as scalability for intricate designs and significant human intervention, leading to prolonged verification durations. As an alternative approach, hardware fuzzing, inspired by software testing methodologies, has gained prominence for its efficacy in identifying bugs within complex hardware designs. Despite the introduction of various hardware fuzzing techniques, obstacles such as inefficient conversion of hardware modules into software models impede their effectiveness. This Systematization of Knowledge (SoK) initiative delves into the fundamental principles of existing hardware fuzzing, methodologies, and their applicability across diverse hardware designs. Additionally, it evaluates factors such as the utilization of golden reference models (GRMs), coverage metrics, and toolchains to gauge their potential for broader adoption, akin to traditional formal verification methods. Furthermore, this work examines the reliability of existing hardware fuzzing techniques in identifying vulnerabilities and identifies research gaps for future advancements in design verification techniques.