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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Try to Poison My Deep Learning Data? Nowhere to...

Yansong Gao (The University of Western Australia), Huaibing Peng (Nanjing University of Science and Technology), Hua Ma (CSIRO's Data61), Zhi Zhang (The University of Western Australia), Shuo Wang (Shanghai Jiao Tong University), Rayne Holland (CSIRO's Data61), Anmin Fu (Nanjing University of Science and Technology), Minhui Xue (CSIRO's Data61), Derek Abbott (The University of Adelaide, Australia)

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Power-Related Side-Channel Attacks using the Android Sensor Framework

Mathias Oberhuber (Graz University of Technology), Martin Unterguggenberger (Graz University of Technology), Lukas Maar (Graz University of Technology), Andreas Kogler (Graz University of Technology), Stefan Mangard (Graz University of Technology)

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LLMPirate: LLMs for Black-box Hardware IP Piracy

Vasudev Gohil (Texas A&M University), Matthew DeLorenzo (Texas A&M University), Veera Vishwa Achuta Sai Venkat Nallam (Texas A&M University), Joey See (Texas A&M University), Jeyavijayan Rajendran (Texas A&M University)

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