Systematic Review of Fuzzing in IoT: Evaluating Techniques, Vulnerabilities, and Research Gaps

Abstract

As our dependence on the internet and digital platforms grows, the risk of cyber threats rises, making it essential to implement effective Measures to safeguard sensitive information through cybersecurity, ensure system integrity, and prevent unauthorized data access. Fuzz testing, commonly known as fuzzing, is a valuable for software testing as it uncovers vulnerabilities and defects in systems by introducing random data inputs, often leading to system crashes. In the Internet of Things domain, fuzzing is crucial for identifying vulnerabilities in networks, devices, and applications through automated tools that systematically inject malformed inputs into IoT systems. This research aims to comprehensively evaluate current fuzzing practices, emphasizing adaptive techniques tailored to IoT environments. A rigorous analysis of 30 recent academic articles was conducted to identify weaknesses, gaps, and challenges in existing approaches. The investigation revealed the need for novel fuzzing techniques that address firmware, hardware, and software vulnerabilities, as well as Denial of Service attacks in IoT systems. By exploring recent trends and identifying gaps and challenges, this research aims to advance IoT security, highlighting the need for improved fuzzing techniques and presenting future research directions to strengthen IoT cybersecurity.