5 citations · 9 across the 9 of their papers we have counts for
5 papers · 1 filter
GraphFaaS: Serverless GNN Inference for Burst-Resilient, Real-Time Intrusion Detection
Lingzhi Wang, Vinod Yegneswaran, Xinyi Shi +3
Provenance-based intrusion detection is an increasingly popular application of graphical machine learning in cybersecurity, where system activities are modeled as provenance graphs…
MobiLLM: An Agentic AI Framework for Closed-Loop Threat Mitigation in 6G Open RANs
Prakhar Sharma, Haohuang Wen, Vinod Yegneswaran +3
The evolution toward 6G networks is being accelerated by the Open Radio Access Network (O-RAN) paradigm -- an open, interoperable architecture that enables intelligent, modular app…
Interpreting Agent Behaviors in Reinforcement-Learning-Based Cyber-Battle Simulation Platforms
Jared Claypoole, Steven Cheung, Ashish Gehani +2
We analyze two open source deep reinforcement learning agents submitted to the CAGE Challenge 2 cyber defense challenge, where each competitor submitted an agent to defend a simula…
Xanthus: Push-button Orchestration of Host Provenance Data Collection
Xueyuan Han, James Mickens, Ashish Gehani +2
Host-based anomaly detectors generate alarms by inspecting audit logs for suspicious behavior. Unfortunately, evaluating these anomaly detectors is hard. There are few high-quality…
ProvMark: A Provenance Expressiveness Benchmarking System
Sheung Chi Chan, James Cheney, Pramod Bhatotia +5
System level provenance is of widespread interest for applications such as security enforcement and information protection. However, testing the correctness or completeness of prov…