Capability hardware enhanced instructions and artificial intelligence bill of materials in trustworthy artificial intelligence systems: analyzing cybersecurity threats, exploits, and vulnerabilities in new software bills of materials with artificial intelligence

Abstract

Integrating Capability-based Hierarchical Embedded RISC Instructions (CHERI) with the Artificial Intelligence (AI) Bill of Materials (AI BOMs) aims to enhance security and transparency in generative AI systems. With the increasing prevalence of AI and machine learning (ML), greater transparency and traceability are essential. This study introduces an analysis to explore how CHERI’s advanced security features can improve the reliability and transparency of AI BOMs, significantly contributing to the overall security of AI and ML technologies. The research employs a multi-faceted approach, combining theoretical analysis with practical evaluations. It begins with a comprehensive review of the existing literature on AI BOMs and CHERI, followed by an in-depth examination of cybersecurity threats, exploits, and vulnerabilities in new Software Bills of Materials (SBOMs). The study leverages AI methodologies, including data analysis techniques and AI-driven simulations, to assess the impact of integrating CHERI’s security features into AI BOMs. The study analyzes how CHERI and AI BOMs can enhance AI system security. The objectives include evaluating the role of AI BOMs in ensuring trust and quality in AI systems, assessing the efficacy of CHERI’s security features in mitigating cybersecurity threats, and identifying and analyzing cybersecurity threats, exploits, and vulnerabilities in SBOMs using AI techniques. The findings demonstrate that integrating CHERI with AI BOMs significantly enhances the security and transparency of AI systems. This integration helps identify and mitigate specific threats and vulnerabilities, improves trust and security in AI systems, and shows the potential of AI-driven methodologies in enhancing the security of SBOMs. By combining CHERI with AI BOMs, a promising pathway is established for creating more secure and transparent AI systems, addressing current cybersecurity challenges, and paving the way for future advancements in AI and ML technologies.