8 citations · 13 across the 4 of their papers we have counts for
9 papers
Learning from Context: Exploiting and Interpreting File Path Information for Better Malware Detection
Adarsh Kyadige, Ethan M. Rudd, Konstantin Berlin
Machine learning (ML) used for static portable executable (PE) malware detection typically employs per-file numerical feature vector representations as input with one or more targe…
Automatic Malware Description via Attribute Tagging and Similarity Embedding
Felipe N. Ducau, Ethan M. Rudd, Tad M. Heppner +2
With the rapid proliferation and increased sophistication of malicious software (malware), detection methods no longer rely only on manually generated signatures but have also inco…
ALOHA: Auxiliary Loss Optimization for Hypothesis Augmentation
Ethan M. Rudd, Felipe N. Ducau, Cody Wild +2
Malware detection is a popular application of Machine Learning for Information Security (ML-Sec), in which an ML classifier is trained to predict whether a given file is malware or…
Toward Open-Set Face Recognition
Manuel Günther, Steve Cruz, Ethan M. Rudd +1
Much research has been conducted on both face identification and face verification, with greater focus on the latter. Research on face identification has mostly focused on using cl…
Automated U.S Diplomatic Cables Security Classification: Topic Model Pruning vs. Classification Based on Clusters
Khudran Alzhrani, Ethan M. Rudd, C. Edward Chow +1
The U.S Government has been the target for cyber-attacks from all over the world. Just recently, former President Obama accused the Russian government of the leaking emails to Wiki…
Open Set Intrusion Recognition for Fine-Grained Attack Categorization
Steve Cruz, Cora Coleman, Ethan M. Rudd +1
Confidently distinguishing a malicious intrusion over a network is an important challenge. Most intrusion detection system evaluations have been performed in a closed set protocol…