Alexandra Weber (Telespazio Germany GmbH), Peter Franke (Telespazio Germany GmbH)

Space missions increasingly rely on Artificial Intelligence (AI) for a variety of tasks, ranging from planning and monitoring of mission operations, to processing and analysis of mission data, to assistant systems like, e.g., a bot that interactively supports astronauts on the International Space Station. In general, the use of AI brings about a multitude of security threats. In the space domain, initial attacks have already been demonstrated, including, e.g., the Firefly attack that manipulates automatic forest-fire detection using sensor spoofing. In this article, we provide an initial analysis of specific security risks that are critical for the use of AI in space and we discuss corresponding security controls and mitigations. We argue that rigorous risk analyses with a focus on AI-specific threats will be needed to ensure the reliability of future AI applications in the space domain.

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Eric Dull, Drew Walsh, Scott Riede (Deloitte and Touche)

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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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LMSanitator: Defending Prompt-Tuning Against Task-Agnostic Backdoors

Chengkun Wei (Zhejiang University), Wenlong Meng (Zhejiang University), Zhikun Zhang (CISPA Helmholtz Center for Information Security and Stanford University), Min Chen (CISPA Helmholtz Center for Information Security), Minghu Zhao (Zhejiang University), Wenjing Fang (Ant Group), Lei Wang (Ant Group), Zihui Zhang (Zhejiang University), Wenzhi Chen (Zhejiang University)

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FP-Fed: Privacy-Preserving Federated Detection of Browser Fingerprinting

Meenatchi Sundaram Muthu Selva Annamalai (University College London), Igor Bilogrevic (Google), Emiliano De Cristofaro (University of California, Riverside)

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