2 citations · 4 across the 8 of their papers we have counts for
8 papers
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…
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…
OblivCDN: A Practical Privacy-preserving CDN with Oblivious Content Access
Viet Vo, Shangqi Lai, Xingliang Yuan +2
Content providers increasingly utilise Content Delivery Networks (CDNs) to enhance users' content download experience. However, this deployment scenario raises significant security…
SoK: The Security-Safety Continuum of Multimodal Foundation Models through Information Flow and Global Game-Theoretic Analysis of Asymmetric Threats
Ruoxi Sun, Jiamin Chang, Hammond Pearce +5
Multimodal foundation models (MFMs) integrate diverse data modalities to support complex and wide-ranging tasks. However, this integration also introduces distinct safety and secur…
SAFE: Advancing Large Language Models in Leveraging Semantic and Syntactic Relationships for Software Vulnerability Detection
Van Nguyen, Surya Nepal, Tingmin Wu +2
Software vulnerabilities (SVs) have emerged as a prevalent and critical concern for safety-critical security systems. This has spurred significant advancements in utilizing AI-base…
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…
RAI4IoE: Responsible AI for Enabling the Internet of Energy
Minhui Xue, Surya Nepal, Ling Liu +5
This paper plans to develop an Equitable and Responsible AI framework with enabling techniques and algorithms for the Internet of Energy (IoE), in short, RAI4IoE. The energy sector…