Core Viewpoint - The article discusses the increasing complexity and challenges of end-to-end security in semiconductor manufacturing, particularly with the rise of multi-chip packaging and edge computing, which complicates supply chain tracking and security measures [1][2][3]. Group 1: Challenges in Multi-Chip Packaging - Multi-chip packaging enhances performance but complicates supply chain tracking, as components may come from different manufacturers [1]. - The aging of chipsets under different workloads can introduce unforeseen vulnerabilities, especially with new components developed using advanced nodes like 3nm [1]. - The fragmentation of chip production among various suppliers increases complexity, making it difficult to ensure compatibility and security across the supply chain [2]. Group 2: Security Measures and Standards - There is a need for comprehensive security measures throughout the supply chain, from chip manufacturing to final product deployment, to mitigate risks associated with malicious chips [3][4]. - The introduction of the EU's Cyber Resilience Act (CRA) mandates companies to assess their security vulnerabilities and supply chain risks, pushing for a more standardized approach to security [5]. - Companies are encouraged to embed unique identifiers in chips to enhance traceability and security [4][5]. Group 3: Long-Term Security Considerations - The longevity of products necessitates ongoing assessments of potential security vulnerabilities that may arise over time [9][10]. - The automotive industry exemplifies the need for long-term security planning, as vehicles may have lifespans of up to 40 years, requiring continuous updates and risk assessments [10]. - Quantum computing poses a future threat to existing encryption methods, necessitating proactive measures during the design phase [9][10]. Group 4: Role of Artificial Intelligence - AI can be utilized to identify security vulnerabilities that are difficult for humans to detect, enhancing the overall security of systems [11]. - However, AI systems themselves require strict controls to prevent independent communication that could compromise security [11][12]. - The development of unified standards for AI in security is still in progress, with organizations working towards establishing comprehensive guidelines [12]. Group 5: Conclusion on Security Landscape - Security has transitioned from a secondary consideration to a primary focus across all stages of electronic system development, with companies facing significant penalties for neglecting security [12]. - Achieving true end-to-end security remains uncertain, but the motivation for companies to pursue it has increased alongside the challenges they face [12].