9 papers
MATRA: Modeling the Attack Surface of Agentic AI Systems -- OpenClaw Case Study
Tim Van hamme, Thomas Vissers, Javier Carnerero-Cano +4
LLMs are increasingly deployed as autonomous agents with access to tools, databases, and external services, yet practitioners (across different sectors) lack systematic methods to…
CLaRE-ty Amid Chaos: Quantifying Representational Entanglement to Predict Ripple Effects in LLM Editing
Manit Baser, Alperen Yildiz, Dinil Mon Divakaran +1
The static knowledge representations of large language models (LLMs) inevitably become outdated or incorrect over time. While model-editing techniques offer a promising solution by…
ThinkEval: Practical Evaluation of Knowledge Leakage in LLM Editing using Thought-based Knowledge Graphs
Manit Baser, Dinil Mon Divakaran, Mohan Gurusamy
Robust model-editing techniques are essential for deploying large language models (LLMs) in practical applications, as they enable cost-effective ways to deal with challenges such…
AI-based Traffic Modeling for Network Security and Privacy: Challenges Ahead
Dinil Mon Divakaran
Network traffic analysis using AI (machine learning and deep learning) models made significant progress over the past decades. Traffic analysis addresses various challenging proble…
RECTor: Robust and Efficient Correlation Attack on Tor
Binghui Wu, Dinil Mon Divakaran, Levente Csikor +1
Tor is a widely used anonymity network that conceals user identities by routing traffic through encrypted relays, yet it remains vulnerable to traffic correlation attacks that dean…
UniNet: A Unified Multi-granular Traffic Modeling Framework for Network Security
Binghui Wu, Dinil Mon Divakaran, Mohan Gurusamy
As modern networks grow increasingly complex--driven by diverse devices, encrypted protocols, and evolving threats--network traffic analysis has become critically important. Existi…