48,240 Malware samples and Binary Visualisation Images for Machine Learning Anomaly Detection

Citation Author(s):
Betty
Saridou
Democritus University of Thrace
Joseph
Rose
The University of Portsmouth
Stavros
Shiaeles
The University of Portsmouth
Basil
Papadopoulos
Democritus University of Thrace
Submitted by:
Joseph Rose
Last updated:
Wed, 06/02/2021 - 19:00
DOI:
10.21227/vs0r-8s26
Data Format:
License:
0
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Abstract 

Dataset including over 40,000 generated images of malicious binaries for malware classification in machine learning as outlined in NARAD - A Novel Auto-learn Real-time Fuzzy Machine Learning Anomaly Detection and Classification System.

Instructions: 

Images used for classification of malware using fuzzy logic in binary visulisaiton. 

Comments

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Submitted by Mirsat Yesiltepe on Fri, 05/14/2021 - 14:30

33

Submitted by Sriram C on Sat, 05/29/2021 - 07:49

Apologies. We had an issue uploading the datasets on IEEE due to the large file sizes. Now you should be able to download them.

Submitted by Joseph Rose on Wed, 06/02/2021 - 18:56

Hi Authors,

Could you explain what is the difference between Malware files and Malicious files? Do you have any elaborated description the dataset?

Thanks

Submitted by Tarek Gaber on Tue, 06/08/2021 - 17:53