This work proposes a hybrid detection framework that integrates event-driven object tracking with targeted, periodic analysis to efficiently identify UI integrity violations, providing an effective and scalable defense against critical XR UI security threats.
Bertram Liu, Vamsi Shankar Simhadri, Daisuke Mashima et al.· Proceedings of the Second Wo...· 0 citations
With more than 20,000 Common Vulnerabilities and Exposures (CVEs) reported annually, software vulnerabilities represent a critical cybersecurity challenge. This volume has intensified the demand for automated detection and analysis, motivating the integration of large language models (LLMs) for such tasks. However, exi...
Vishnu Teja Kandalam, Viet Duong, Xiaochang Li et al.· Proceedings of the 32nd ACM...· 0 citations
An evaluation of five state-of-the-art LLMs on OmniVul reveals distinct performance gaps, with top-1 accuracy remaining below 50% on average for vulnerable code detection and CVE identification, demonstrating that current models lack critical reasoning capabilities for reliable vulnerability assessment.
Vishnu Teja Kandalam, Viet Duong, Xiaochang Li et al.· Proceedings of the 32nd ACM...· 0 citations
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