Investigation of Firmware Securing IoT Devices at the Chip Level Using AI and ML Approaches: A Concise Systematic Literature Review

Abstract

System-on-Chip (SoC) designs are becoming increasingly intricate as they integrate various components and functionalities onto a single chip. This intricacy brings forth new vulnerabilities and attack surfaces, presenting a challenging task to ensure robust cybersecurity. Although previous studies have explored different AI approaches, there is a need to delve into the complexities of modern SoCs and propose practical methods to secure these systems, thereby aiding researchers in mitigating potential threats. The primary objective of this paper is to uncover the opportunities that emerge from utilizing AI techniques in SoC designs to fortify cybersecurity defenses. Subsequently, the study aims to deliberate on the complexities involved in integrating AI with SoC and provide appropriate recommendations to address these intricacies. This review paper will identify and discuss the technical, architectural, and implementation challenges faced by researchers and practitioners when incorporating AI into SoC designs for cybersecurity purposes. Moreover, it will suggest with potential solutions and strategies to effectively tackle these challenges. Furthermore, it aims to aid future researchers by offering potential research directions to enhance security in AI-SoC through innovative solutions. By identifying gaps in current literature and highlighting areas that require further exploration, this paper will guide future researchers in developing advanced and secure AI-SoC systems for cybersecurity applications. Overall, this review paper will contribute to the existing body of knowledge by providing a comprehensive analysis of the impact that integrating AI and SoC has on cybersecurity and foster advancements in AI-SoC systems that effectively enhance cybersecurity measures.