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…
REFN: A Reinforcement-Learning-From-Network Framework against 1-day/n-day Exploitations
Tianlong Yu, Lihong Liu, Ziyi Zhou +3
The exploitation of 1 day or n day vulnerabilities poses severe threats to networked devices due to massive deployment scales and delayed patching (average Mean Time To Patch excee…
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…