8 citations · 18 across the 10 of their papers we have counts for
10 papers
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…
Augmenting Rule-based DNS Censorship Detection at Scale with Machine Learning
Jacob Brown, Xi Jiang, Van Tran +5
The proliferation of global censorship has led to the development of a plethora of measurement platforms to monitor and expose it. Censorship of the domain name system (DNS) is a k…
Scalable Microservice Forensics and Stability Assessment Using Variational Autoencoders
Prakhar Sharma, Phillip Porras, Steven Cheung +2
We present a deep learning based approach to containerized application runtime stability analysis, and an intelligent publishing algorithm that can dynamically adjust the depth of…
On the Privacy and Integrity Risks of Contact-Tracing Applications
Jianwei Huang, Vinod Yegneswaran, Phillip Porras +1
Smartphone-based contact-tracing applications are at the epicenter of the global fight against the Covid-19 pandemic. While governments and healthcare agencies are eager to mandate…
VISCR: Intuitive & Conflict-free Automation for Securing the Dynamic Consumer IoT Infrastructures
Vasudevan Nagendra, Arani Bhattacharya, Vinod Yegneswaran +2
Consumer IoT is characterized by heterogeneous devices with diverse functionality and programming interfaces. This lack of homogeneity makes the integration and security management…
Data Masking with Privacy Guarantees
Anh T. Pham, Shalini Ghosh, Vinod Yegneswaran
We study the problem of data release with privacy, where data is made available with privacy guarantees while keeping the usability of the data as high as possible --- this is impo…
Time Series Deinterleaving of DNS Traffic
Amir Asiaee, Hardik Goel, Shalini Ghosh +2
Stream deinterleaving is an important problem with various applications in the cybersecurity domain. In this paper, we consider the specific problem of deinterleaving DNS data stre…
Trusted Neural Networks for Safety-Constrained Autonomous Control
Shalini Ghosh, Amaury Mercier, Dheeraj Pichapati +3
We propose Trusted Neural Network (TNN) models, which are deep neural network models that satisfy safety constraints critical to the application domain. We investigate different me…