4 papers
PhySE: A Psychological Framework for Real-Time AR-LLM Social Engineering Attacks
Tianlong Yu, Yang Yang, Ziyi Zhou +5
The emerging threat of AR-LLM-based Social Engineering (AR-LLM-SE) attacks (e.g. SEAR) poses a significant risk to real-world social interactions. In such an attack, a malicious ac…
UNSEEN: A Cross-Stack LLM Unlearning Defense against AR-LLM Social Engineering Attacks
Tianlong Yu, Yang Yang, Xiao Luo +6
Emerging AR-LLM-based Social Engineering attack (e.g., SEAR) is at the edge of posing great threats to real-world social life. In such AR-LLM-SE attack, the attacker can leverage A…
SEAR: A Multimodal Dataset for Analyzing AR-LLM-Driven Social Engineering Behaviors
Tianlong Yu, Chenghang Ye, Zheyu Yang +8
The SEAR Dataset is a novel multimodal resource designed to study the emerging threat of social engineering (SE) attacks orchestrated through augmented reality (AR) and multimodal…
On the Feasibility of Using MultiModal LLMs to Execute AR Social Engineering Attacks
Ting Bi, Chenghang Ye, Zheyu Yang +8
Augmented Reality (AR) and Multimodal Large Language Models (LLMs) are rapidly evolving, providing unprecedented capabilities for human-computer interaction. However, their integra…