152 citations · 225 across the 5 of their papers we have counts for
7 papers
Machine Learning Algorithms for Active Monitoring of High Performance Computing as a Service (HPCaaS) Cloud Environments
Gianluca Longoni, Ryan LaMothe, Jeremy Teuton +3
Cloud computing provides ubiquitous and on-demand access to vast reconfigurable resources that can meet any computational need. Many service models are available, but the Infrastru…
Systematic Evaluation of Backdoor Data Poisoning Attacks on Image Classifiers
Loc Truong, Chace Jones, Brian Hutchinson +5
Backdoor data poisoning attacks have recently been demonstrated in computer vision research as a potential safety risk for machine learning (ML) systems. Traditional data poisoning…
Projecting Trouble: Light Based Adversarial Attacks on Deep Learning Classifiers
Nicole Nichols, Robert Jasper
This work demonstrates a physical attack on a deep learning image classification system using projected light onto a physical scene. Prior work is dominated by techniques for creat…
Recurrent Neural Network Attention Mechanisms for Interpretable System Log Anomaly Detection
Andy Brown, Aaron Tuor, Brian Hutchinson +1
Deep learning has recently demonstrated state-of-the art performance on key tasks related to the maintenance of computer systems, such as intrusion detection, denial of service att…
Recurrent Neural Network Language Models for Open Vocabulary Event-Level Cyber Anomaly Detection
Aaron Tuor, Ryan Baerwolf, Nicolas Knowles +3
Automated analysis methods are crucial aids for monitoring and defending a network to protect the sensitive or confidential data it hosts. This work introduces a flexible, powerful…
Faster Fuzzing: Reinitialization with Deep Neural Models
Nicole Nichols, Mark Raugas, Robert Jasper +1
We improve the performance of the American Fuzzy Lop (AFL) fuzz testing framework by using Generative Adversarial Network (GAN) models to reinitialize the system with novel seed fi…