4 citations · 5 across the 9 of their papers we have counts for
10 papers
parHSOM: A novel parallel Hierarchical Self-Organizing Map implementation
Rebekah Lane, Logan Cummins, Andy Perkins +3
The digital age has completely transformed the way that information is processed and stored, which makes cybersecurity a crucial field of research. Cybersecurity contains many diff…
A Survey on Adversarial Contention Resolution
Ioana Banicescu, Trisha Chakraborty, Seth Gilbert +1
Contention resolution addresses the challenge of coordinating access by multiple processes to a shared resource such as memory, disk storage, or a communication channel. Originally…
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…
Two-level Dynamic Load Balancing for High Performance Scientific Applications
Ali Mohammed, Aurelien Cavelan, Florina M. Ciorba +2
Scientific applications are often complex, irregular, and computationally-intensive. To accommodate the ever-increasing computational demands of scientific applications, high-perfo…
An Approach for Realistically Simulating the Performance of Scientific Applications on High Performance Computing Systems
Ali Mohammed, Ahmed Eleliemy, Florina M. Ciorba +2
Scientific applications often contain large, computationally-intensive, and irregular parallel loops or tasks that exhibit stochastic characteristics. Applications may suffer from…
Experimental Verification and Analysis of Dynamic Loop Scheduling in Scientific Applications
Ali Mohammed, Ahmed Eleliemy, Florina M. Ciorba +2
Scientific applications are often irregular and characterized by large computationally-intensive parallel loops. Dynamic loop scheduling (DLS) techniques improve the performance of…