ChaeYoung Kim (Seoul Women's University), Kyounggon Kim (Naif Arab University for Security Sciences)

The integration of robotics and IoT technologies into everyday systems has revolutionized smart environments while introducing critical security and privacy challenges. This paper presents FORESIGHT, a unified framework for threat modeling and risk assessment, that addresses vulnerabilities in autonomous robotics and IoT ecosystems. By categorizing threats into robot-oriented, user-oriented, and environmental domains, FORESIGHT enables comprehensive risk analysis and prioritization of high-risk threats. Using Bayesian networks, the framework evaluates cascading vulnerabilities and interdependencies across system layers. Aligned with international standards such as ISO 13482, IEC 62443, and GDPR, FORESIGHT ensures a structured approach to improving the resilience of humancentered interconnected systems.

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Stacking up the LLM Risks: Applied Machine Learning Security

Dr. Gary McGraw, Berryville Institute of Machine Learning

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Mysticeti: Reaching the Latency Limits with Uncertified DAGs

Kushal Babel (Cornell Tech & IC3), Andrey Chursin (Mysten Labs), George Danezis (Mysten Labs & University College London (UCL)), Anastasios Kichidis (Mysten Labs), Lefteris Kokoris-Kogias (Mysten Labs & IST Austria), Arun Koshy (Mysten Labs), Alberto Sonnino (Mysten Labs & University College London (UCL)), Mingwei Tian (Mysten Labs)

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