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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Probe-Me-Not: Protecting Pre-trained Encoders from Malicious Probing

Ruyi Ding (Northeastern University), Tong Zhou (Northeastern University), Lili Su (Northeastern University), Aidong Adam Ding (Northeastern University), Xiaolin Xu (Northeastern University), Yunsi Fei (Northeastern University)

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I Know What You Asked: Prompt Leakage via KV-Cache...

Guanlong Wu (Southern University of Science and Technology), Zheng Zhang (ByteDance Inc.), Yao Zhang (ByteDance Inc.), Weili Wang (Southern University of Science and Technolog), Jianyu Niu (Southern University of Science and Technolog), Ye Wu (ByteDance Inc.), Yinqian Zhang (Southern University of Science and Technology (SUSTech))

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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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