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

no code implementations • 12 Jun 2018 • William Fleshman, Edward Raff, Richard Zak, Mark McLean, Charles Nicholas

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) systems widely used today.

BIG-bench Machine Learning Malware Detection

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

no code implementations • 7 May 2019 • Aditya Pingle, Aritran Piplai, Sudip Mittal, Anupam Joshi, James Holt, Richard Zak

A cybersecurity knowledge graph can be paramount in aiding a security analyst to detect cyber threats because it stores a vast range of cyber threat information in the form of semantic triples which can be queried.

Relation Relation Extraction

KiloGrams: Very Large N-Grams for Malware Classification

1 code implementation • 1 Aug 2019 • Edward Raff, William Fleming, Richard Zak, Hyrum Anderson, Bill Finlayson, Charles Nicholas, Mark McLean

N-grams have been a common tool for information retrieval and machine learning applications for decades.

Classification General Classification +4

Automatic Yara Rule Generation Using Biclustering

1 code implementation • 6 Sep 2020 • Edward Raff, Richard Zak, Gary Lopez Munoz, William Fleming, Hyrum S. Anderson, Bobby Filar, Charles Nicholas, James Holt

Yara rules are a ubiquitous tool among cybersecurity practitioners and analysts.

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

1 code implementation • 17 Dec 2020 • Edward Raff, William Fleshman, Richard Zak, Hyrum S. Anderson, Bobby Filar, Mark McLean

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

Malware Detection Time Series +1