activity
20222026
most citedA Machine Learning and Computer Vision Approach to Geomagnetic Storm Forecasting

3 citations · 4 across the 6 of their papers we have counts for

collaborators
Showing cs.CRShow all

5 papers · 1 filter

cs.CR2026

MESA: Prioritizing Vulnerable Communication Channels for Securing Multi-Agent Systems

Kunyang Li, Kyle Domico, Jonathan Gregory +1

Multi-agent systems (MAS) are increasingly used to automate complex, distributed workflows. However, their inter-agent communication channels introduce new attack surfaces that rem…

cs.CR2026

Longitudinal Analyses of SAST Tools: A CodeQL Case Study

Jean-Charles Noirot Ferrand, Kyle Domico, Yohan Beugin +1

Open-source software (OSS) pipelines rely on automated static analysis tools to prevent the introduction of vulnerabilities in code. However, there is limited understanding of the…

cs.CR2026

The Role of Learning in Attacking ML-based Network Intrusion Detection

Kyle Domico, Jean-Charles Noirot Ferrand, Patrick McDaniel

Machine learning (ML)-based network intrusion detection is susceptible to attacks that perturb malicious network flows to evade detection. Existing approaches to evaluating the rob…

cs.CR20251 cited

Adversarial Agents: Black-Box Evasion Attacks with Reinforcement Learning

Kyle Domico, Jean-Charles Noirot Ferrand, Ryan Sheatsley +3

Attacks on machine learning models have been extensively studied through stateless optimization. In this paper, we demonstrate how a reinforcement learning (RL) agent can learn a n…

cs.CR2023

The Efficacy of Transformer-based Adversarial Attacks in Security Domains

Kunyang Li, Kyle Domico, Jean-Charles Noirot Ferrand +1

Today, the security of many domains rely on the use of Machine Learning to detect threats, identify vulnerabilities, and safeguard systems from attacks. Recently, transformer archi…