1 citations · 2 across the 9 of their papers we have counts for
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Automated Penetration Testing with LLM Agents and Classical Planning
Lingzhi Wang, Xinyi Shi, Ziyu Li +8
While penetration testing plays a vital role in cybersecurity, achieving fully automated, hands-off-the-keyboard execution remains a significant research challenge. In this paper,…
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…
AEAS: Actionable Exploit Assessment System
Xiangmin Shen, Wenyuan Cheng, Yan Chen +6
Security practitioners face growing challenges in exploit assessment, as public vulnerability repositories are increasingly populated with inconsistent and low-quality exploit arti…
PARIS: A Practical, Adaptive Trace-Fetching and Real-Time Malicious Behavior Detection System
Jian Wang, Lingzhi Wang, Husheng Yu +2
The escalating sophistication of cyber-attacks and the widespread utilization of stealth tactics have led to significant security threats globally. Nevertheless, the existing stati…
PentestAgent: Incorporating LLM Agents to Automated Penetration Testing
Xiangmin Shen, Lingzhi Wang, Zhenyuan Li +5
Penetration testing is a critical technique for identifying security vulnerabilities, traditionally performed manually by skilled security specialists. This complex process involve…
From Sands to Mansions: Towards Automated Cyberattack Emulation with Classical Planning and Large Language Models
Lingzhi Wang, Zhenyuan Li, Yi Jiang +4
Evolving attacker capabilities demand realistic and continuously updated cyberattack emulation for threat-informed defense and security benchmarking. Towards automated attack emula…
Incorporating Gradients to Rules: Towards Lightweight, Adaptive Provenance-based Intrusion Detection
Lingzhi Wang, Xiangmin Shen, Weijian Li +4
As cyber attacks grow increasingly sophisticated and stealthy, it becomes more imperative and challenging to detect intrusion from normal behaviors. Through fine-grained causality…
Marlin: Knowledge-Driven Analysis of Provenance Graphs for Efficient and Robust Detection of Cyber Attacks
Zhenyuan Li, Yangyang Wei, Xiangmin Shen +9
Recent research in both academia and industry has validated the effectiveness of provenance graph-based detection for advanced cyber attack detection and investigation. However, an…
Decoding the MITRE Engenuity ATT&CK Enterprise Evaluation: An Analysis of EDR Performance in Real-World Environments
Xiangmin Shen, Zhenyuan Li, Graham Burleigh +2
Endpoint detection and response (EDR) systems have emerged as a critical component of enterprise security solutions, effectively combating endpoint threats like APT attacks with ex…