182 citations · 209 across the 2 of their papers we have counts for
5 papers
Automatic Yara Rule Generation Using Biclustering
Edward Raff, Richard Zak, Gary Lopez Munoz +5
Yara rules are a ubiquitous tool among cybersecurity practitioners and analysts. Developing high-quality Yara rules to detect a malware family of interest can be labor- and time-in…
KiloGrams: Very Large N-Grams for Malware Classification
Edward Raff, William Fleming, Richard Zak +4
N-grams have been a common tool for information retrieval and machine learning applications for decades. In nearly all previous works, only a few values of are tested, with $n…
Detecting Homoglyph Attacks with a Siamese Neural Network
Jonathan Woodbridge, Hyrum S. Anderson, Anjum Ahuja +1
A homoglyph (name spoofing) attack is a common technique used by adversaries to obfuscate file and domain names. This technique creates process or domain names that are visually si…
EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models
Hyrum S. Anderson, Phil Roth
This paper describes EMBER: a labeled benchmark dataset for training machine learning models to statically detect malicious Windows portable executable files. The dataset includes…
Learning to Evade Static PE Machine Learning Malware Models via Reinforcement Learning
Hyrum S. Anderson, Anant Kharkar, Bobby Filar +2
Machine learning is a popular approach to signatureless malware detection because it can generalize to never-before-seen malware families and polymorphic strains. This has resulted…