4 citations · 5 across the 5 of their papers we have counts for
5 papers · 1 filter
Eclectic Rule Extraction for Explainability of Deep Neural Network based Intrusion Detection Systems
Jesse Ables, Nathaniel Childers, William Anderson +4
This paper addresses trust issues created from the ubiquity of black box algorithms and surrogate explainers in Explainable Intrusion Detection Systems (X-IDS). While Explainable A…
Explainable Intrusion Detection Systems Using Competitive Learning Techniques
Jesse Ables, Thomas Kirby, Sudip Mittal +4
The current state of the art systems in Artificial Intelligence (AI) enabled intrusion detection use a variety of black box methods. These black box methods are generally trained u…
Designing an Artificial Immune System inspired Intrusion Detection System
William Anderson, Kaneesha Moore, Jesse Ables +4
The Human Immune System (HIS) works to protect a body from infection, illness, and disease. This system can inspire cybersecurity professionals to design an Artificial Immune Syste…
Creating an Explainable Intrusion Detection System Using Self Organizing Maps
Jesse Ables, Thomas Kirby, William Anderson +4
Modern Artificial Intelligence (AI) enabled Intrusion Detection Systems (IDS) are complex black boxes. This means that a security analyst will have little to no explanation or clar…
Explainable Intrusion Detection Systems (X-IDS): A Survey of Current Methods, Challenges, and Opportunities
Subash Neupane, Jesse Ables, William Anderson +4
The application of Artificial Intelligence (AI) and Machine Learning (ML) to cybersecurity challenges has gained traction in industry and academia, partially as a result of widespr…