Microsoft Malware Classification Challenge

By Royi Ronen, Marian Radu, Corina Feuerstein, Elad Yom-Tov, Mansour Ahmadi. arXiv.org, 2018

428 citations recorded by the source corpus.

The Microsoft Malware Classification Challenge was announced in 2015 along with a publication of a huge dataset of nearly 0.5 terabytes, consisting of disassembly and bytecode of more than 20K malware samples. Apart from serving in the Kaggle competition, the dataset has become a standard benchmark for research on modeling malware behaviour. To date, the dataset has been cited in more than 50 research papers. Here we provide a high-level comparison of the publications citing the dataset. The comparison simplifies finding potential research directions in this field and future performance evaluation of the dataset.

Subfields: Artificial Intelligence, Computer Networks and Communications, Signal Processing

View Paper: https://www.semanticscholar.org/paper/7f33275e65f9774bab55f1e484a8ed8526e8fb9a

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Artificial Intelligence

1. Ömer Aslan
2. Phil Roth
3. Refik Samet
4. H. S. Anderson

In Computer Networks and Communications

1. Ömer Aslan
2. Phil Roth
3. Refik Samet
4. H. S. Anderson

In Signal Processing

1. Ömer Aslan
2. Phil Roth
3. Refik Samet
4. H. S. Anderson

Citations in the corpus

• A Comprehensive Review on Malware Detection Approaches (2020, methodology): “• Microsoft malware classification challenge dataset (2015): It has been published by Microsoft and consists of 20,000 malware [24].”
• EMBER: An Open Dataset for Training Static PE Malware Machine Learning Models (2018, methodology): “In contrast, the Microsoft Malware Classification Challenge concluded in April 2015 [25].”