Security in Artificial Intelligence White Paper
Presented by the Intellectual Property Interest Group of the Global Semiconductor Alliance, with contributions by Frank Schirrmeister, VP of Solutions and Business Development at Arteris.
In the rapidly evolving landscape of Artificial Intelligence (AI), the "Security in AI" whitepaper offers a comprehensive analysis of the security challenges unique to AI systems. As AI integrates deeper into various sectors, its security becomes paramount. This paper examines the vulnerabilities inherent to AI, from IP protection to supply chain security, and proposes robust strategies to safeguard these systems against a spectrum of cyber threats.
In this white paper, learn more about:
- Unique Security Challenges of AI Systems: AI systems present distinct security challenges, including protecting AI intellectual property (IP), ensuring the integrity of AI training sets, and safeguarding the supply chain of AI components. The paper emphasizes the need for innovative and AI-specific security solutions to mitigate these risks effectively.
- Protection Strategies for AI Systems: The whitepaper outlines strategies for protecting AI systems. These include enhancing the confidentiality, integrity, and availability of AI IP, employing secure development practices, and implementing intrusion detection systems. Additionally, it stresses the importance of continuous improvement in security measures to adapt to evolving threats in the AI landscape.
- AI's Role in Enhancing Cybersecurity: The paper also explores how AI can be leveraged to improve cybersecurity. AI's capabilities in automating threat detection and response can significantly augment existing security frameworks, creating a synergistic relationship where AI poses security challenges and forms part of the solution. This highlights the dual role of AI as both a subject and a tool in cybersecurity.
As part of the hardware foundation of AI systems, Networks-on-Chips (NoCs) are critical to ensuring safety and security.
