From the 1 of 46 linked papers with an AI index.
11 papers · 1 filter
Trident : How to Break Deep Reinforcement Learning Cyber Defenses (Agentic)
Ryozo Masukawa, Ian Bryant, Armita Kazeminajafabadi +6
Autonomous cyber defense systems based on Deep Reinforcement Learning (DRL) have attracted significant research attention, yet remain evaluated almost exclusively against static, h…
Synthetic Network Packet Generation through Statistical Learning and Genetic Algorithms
Mayank Raj, Nathaniel D. Bastian, Lance Fiondella +1
Developing robust intrusion detection systems (IDS) for IoT environments requires large, labeled datasets capturing realistic traffic distributions across both benign and malicious…
Categorical Robustness Assessment for Machine Learning based Network Intrusion Detection Systems
Mayank Raj, Nathaniel D. Bastian, Lance Fiondella +1
Network Intrusion Detection Systems (NIDS) heavily utlize Machine Learning (ML) but ML models can be manipulated via adversarial attacks. These attacks add carefully crafted pertur…
A Red Teaming Framework for Evaluating Robustness of AI-enabled Security Orchestration, Automation, and Response Systems
Ayan Javeed Shaikh, Nathaniel D. Bastian, Ankit Shah
AI-enabled Security Orchestration, Automation, and Response (SOAR) systems increasingly employ autonomous agents for cyber defense, yet their resilience to adaptive adversaries is…
An Automated, Scalable Machine Learning Model Inversion Assessment Pipeline
Tyler Shumaker, Jessica Carpenter, David Saranchak +1
Machine learning (ML) models have the potential to transform military battlefields, presenting a large external pressure to rapidly incorporate them into operational settings. Howe…
Adapting Under Fire: Multi-Agent Reinforcement Learning for Adversarial Drift in Network Security
Emilia Rivas, Sabrina Saika, Ahtesham Bakht +3
Evolving attacks are a critical challenge for the long-term success of Network Intrusion Detection Systems (NIDS). The rise of these changing patterns has exposed the limitations o…