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Attacking Autonomous Driving Agents with Adversarial Machine Learning: A Holistic Evaluation with the CARLA Leaderboard
Henry Wong, Clement Fung, Weiran Lin +3
To autonomously control vehicles, driving agents use outputs from a combination of machine-learning (ML) models, controller logic, and custom modules. Although numerous prior works…
Perry: A High-level Framework for Accelerating Cyber Deception Experimentation
Brian Singer, Yusuf Saquib, Lujo Bauer +1
Cyber deception aims to distract, delay, and detect network attackers with fake assets such as honeypots, decoy credentials, or decoy files. However, today, it is difficult for ope…
Incalmo: An Autonomous LLM-assisted System for Red Teaming Multi-Host Networks
Brian Singer, Keane Lucas, Lakshmi Adiga +3
Security operators use red teams to simulate real attackers and proactively find defense gaps. In realistic enterprise settings, this involves executing multi-host network attacks…
LLM Whisperer: An Inconspicuous Attack to Bias LLM Responses
Weiran Lin, Anna Gerchanovsky, Omer Akgul +3
Writing effective prompts for large language models (LLM) can be unintuitive and burdensome. In response, services that optimize or suggest prompts have emerged. While such service…