activity
20182020
most citedAutomatic Yara Rule Generation Using Biclustering

27 citations · 28 across the 3 of their papers we have counts for

collaborators

5 papers

stat.ML2020

Classifying Sequences of Extreme Length with Constant Memory Applied to Malware Detection

Edward Raff, William Fleshman, Richard Zak +3

Recent works within machine learning have been tackling inputs of ever-increasing size, with cybersecurity presenting sequence classification problems of particularly extreme lengt…

cs.CR202027 cited

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…

cs.CR2019

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…

cs.CL20191 cited

RelExt: Relation Extraction using Deep Learning approaches for Cybersecurity Knowledge Graph Improvement

Aditya Pingle, Aritran Piplai, Sudip Mittal +3

Security Analysts that work in a `Security Operations Center' (SoC) play a major role in ensuring the security of the organization. The amount of background knowledge they have abo…

cs.CR2018

Static Malware Detection & Subterfuge: Quantifying the Robustness of Machine Learning and Current Anti-Virus

William Fleshman, Edward Raff, Richard Zak +2

As machine-learning (ML) based systems for malware detection become more prevalent, it becomes necessary to quantify the benefits compared to the more traditional anti-virus (AV) s…