90 citations · 120 across the 9 of their papers we have counts for
Showing cs.CRShow all
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cs.CR2019★ 8 cited
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…
cs.CR2018★ 1 cited
A Deep Learning Approach to Fast, Format-Agnostic Detection of Malicious Web Content
Joshua Saxe, Richard Harang, Cody Wild +1
Malicious web content is a serious problem on the Internet today. In this paper we propose a deep learning approach to detecting malevolent web pages. While past work on web conten…