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ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: Datacite
image/svg+xml art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos Open Access logo, converted into svg, designed by PLoS. This version with transparent background. http://commons.wikimedia.org/wiki/File:Open_Access_logo_PLoS_white.svg art designer at PLoS, modified by Wikipedia users Nina, Beao, JakobVoss, and AnonMoos http://www.plos.org/
ZENODO
Dataset . 2023
License: CC BY
Data sources: ZENODO
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Dataset for Unsupervised Clustering of CFG Files

Authors: Liyanage, Kaveen; Pearsall, Reese; Izurieta, Clemente; Whitaker, Bradley M.;

Dataset for Unsupervised Clustering of CFG Files

Abstract

This dataset consists of control flow graphs (CFGs) of malware and benign binary files. Due to the security risk of sharing malware binary files online, these binary files are not shared. However, the hash values of the binaries are given for information. The dataset is associated with the software available at https://github.com/MSUSEL/unsupervised-graph (link may change). A manuscript outlining the problem and software solution, titled "Malware Detection Using Unsupervised Clustering of Binary File Control Flow Graphs," is under review for publication in IEEE Transactions on Information Forensics and Security. Upon publication, the related identifiers for both the code and the paper will be updated.

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Keywords

Dataset; Malware Identification; Control Flow Graph

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This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
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influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
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impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
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