Minerva funded researchers, Jeongkeun Shin, L. Richard Carley, and Kathleen M. Carley received “Best Paper Runner Up” at the 2024 Annual Modeling and Simulation Conference (ANNSIM’24) which is an annual conference that covers state-of-the-art developments in Modeling & Simulation (M&S). Each year, ANNSIM recognizes exceptional papers, attendees, and student affiliates with awards which includes the best paper award and the best runner-up paper. The conference accepted 63 papers and the Minerva supported paper, “Simulation-Based Study on False Alarms in Intrusion Detection Systems for Organizations Facing Dual Phishing and DoS Attacks” was selected as the second best. This paper introduces an extremely efficient agent-based modeling and simulation approach to assess the false alarm consequences in machine learning-based Intrusion Detection Systems (IDSs) during dual Denial of Service (DoS) and Phishing attacks. The IDSs with distinct false positive rates, constructed using the KDD-99 dataset with diverse machine learning algorithms, were simulated to analyze how these varying false alarm rates affect the extent of damage caused by Phishing and DoS attacks. The paper is expected to be published late June in the ACM Digital Library and IEEE Digital Library.
Shin, J., L. R. Carley, and K. M. Carley. “Simulation-Based Study on False Alarms in Intrusion Detection Systems for
Organizations Facing Dual Phishing and DoS Attacks”. In 2024 Annual Modeling and Simulation Conference (ANNSIM). Forthcoming.
Associated Minerva-funded Project: Automated Early Warning System for Cyber Intrusion Detection