2 citations · 3 across the 7 of their papers we have counts for
5 papers · 1 filter
Keep the Lights On, Keep the Lengths in Check: Plug-In Adversarial Detection for Time-Series LLMs in Energy Forecasting
Hua Ma, Ruoxi Sun, Minhui Xue +4
Accurate time-series forecasting is increasingly critical for planning and operations in low-carbon power systems. Emerging time-series large language models (TS-LLMs) now deliver…
From Description to Detection: LLM based Extendable O-RAN Compliant Blind DoS Detection in 5G and Beyond
Thusitha Dayaratne, Ngoc Duy Pham, Viet Vo +5
The quality and experience of mobile communication have significantly improved with the introduction of 5G, and these improvements are expected to continue beyond the 5G era. Howev…
MulVuln: Enhancing Pre-trained LMs with Shared and Language-Specific Knowledge for Multilingual Vulnerability Detection
Van Nguyen, Surya Nepal, Xingliang Yuan +3
Software vulnerabilities (SVs) pose a critical threat to safety-critical systems, driving the adoption of AI-based approaches such as machine learning and deep learning for softwar…
Deep Learning-Based Out-of-distribution Source Code Data Identification: How Far Have We Gone?
Van Nguyen, Xingliang Yuan, Tingmin Wu +3
Software vulnerabilities (SVs) have become a common, serious, and crucial concern to safety-critical security systems. That leads to significant progress in the use of AI-based met…
An Innovative Information Theory-based Approach to Tackle and Enhance The Transparency in Phishing Detection
Van Nguyen, Tingmin Wu, Xingliang Yuan +3
Phishing attacks have become a serious and challenging issue for detection, explanation, and defense. Despite more than a decade of research on phishing, encompassing both technica…