Researchers have developed two new frameworks to combat social engineering attacks that leverage augmented reality (AR) and large language models (LLMs). The first, PhySE, uses a visual language model for rapid profile generation and an adaptive psychological agent to tailor social engineering strategies in real-time. The second, UNSEEN, offers a cross-stack defense combining access control on AR devices, LLM unlearning for profile suppression, and runtime agent guardrails. Both frameworks were evaluated in IRB-approved user studies involving 60 participants and 360 annotated conversations. AI
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IMPACT Introduces novel defense mechanisms against sophisticated AR-LLM social engineering, potentially influencing future security protocols.
RANK_REASON Two academic papers proposing novel frameworks for defense against AR-LLM social engineering attacks.