5 papers
AegisMCP: Online Graph Intrusion Detection for Tool-Augmented LLMs on Edge Devices
Zhonghao Zhan, Amir Al Sadi, Krinos Li +1
In this work, we study security of Model Context Protocol (MCP) agent toolchains and their applications in smart homes. We introduce AegisMCP, a protocol-level intrusion detector.…
Large Language Models Meet Virtual Cell: A Survey
Krinos Li, Xianglu Xiao, Shenglong Deng +7
Large language models (LLMs) are transforming cellular biology by enabling the development of "virtual cells"--computational systems that represent, predict, and reason about cellu…
REAL-IoT: Characterizing GNN Intrusion Detection Robustness under Practical Adversarial Attack
Zhonghao Zhan, Huichi Zhou, Hamed Haddadi
Graph Neural Network (GNN)-based network intrusion detection systems (NIDS) are often evaluated on single datasets, limiting their ability to generalize under distribution drift. F…
Poster: Enhancing GNN Robustness for Network Intrusion Detection via Agent-based Analysis
Zhonghao Zhan, Huichi Zhou, Hamed Haddadi
Graph Neural Networks (GNNs) show great promise for Network Intrusion Detection Systems (NIDS), particularly in IoT environments, but suffer performance degradation due to distribu…
TrustRAG: Enhancing Robustness and Trustworthiness in Retrieval-Augmented Generation
Huichi Zhou, Kin-Hei Lee, Zhonghao Zhan +5
Retrieval-Augmented Generation (RAG) enhances large language models (LLMs) by integrating external knowledge sources, enabling more accurate and contextually relevant responses tai…