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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Distributed Function Secret Sharing and Applications

Pengzhi Xing (University of Electronic Science and Technology of China), Hongwei Li (University of Electronic Science and Technology of China), Meng Hao (Singapore Management University), Hanxiao Chen (University of Electronic Science and Technology of China), Jia Hu (University of Electronic Science and Technology of China), Dongxiao Liu (University of Electronic Science and Technology of China)

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QMSan: Efficiently Detecting Uninitialized Memory Errors During Fuzzing

Matteo Marini (Sapienza University of Rome), Daniele Cono D'Elia (Sapienza University of Rome), Mathias Payer (EPFL), Leonardo Querzoni (Sapienza University of Rome)

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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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