13 citations · 27 across the 4 of their papers we have counts for
7 papers
Cybersecurity Anomaly Detection in Adversarial Environments
David A. Bierbrauer, Alexander Chang, Will Kritzer +1
The proliferation of interconnected battlefield information-sharing devices, known as the Internet of Battlefield Things (IoBT), introduced several security challenges. Inherent to…
Advancing the Research and Development of Assured Artificial Intelligence and Machine Learning Capabilities
Tyler J. Shipp, Daniel J. Clouse, Michael J. De Lucia +4
Artificial intelligence (AI) and machine learning (ML) have become increasingly vital in the development of novel defense and intelligence capabilities across all domains of warfar…
Algorithm Selection Framework for Cyber Attack Detection
Marc Chalé, Nathaniel D. Bastian, Jeffery Weir
The number of cyber threats against both wired and wireless computer systems and other components of the Internet of Things continues to increase annually. In this work, an algorit…
Adversarial Machine Learning in Network Intrusion Detection Systems
Elie Alhajjar, Paul Maxwell, Nathaniel D. Bastian
Adversarial examples are inputs to a machine learning system intentionally crafted by an attacker to fool the model into producing an incorrect output. These examples have achieved…
Stacked Generalizations in Imbalanced Fraud Data Sets using Resampling Methods
Kathleen Kerwin, Nathaniel D. Bastian
This study uses stacked generalization, which is a two-step process of combining machine learning methods, called meta or super learners, for improving the performance of algorithm…
Intelligent Systems Design for Malware Classification Under Adversarial Conditions
Sean M. Devine, Nathaniel D. Bastian
The use of machine learning and intelligent systems has become an established practice in the realm of malware detection and cyber threat prevention. In an environment characterize…