Graph-Based Comparison Of Iot And Android Malware
Keywords
Android; Graph analysis; IoT; Malware
Abstract
The growth in the number of android and Internet of Things (IoT) devices has witnessed a parallel increase in the number of malicious software (malware) that can run on both, affecting their ecosystems. Thus, it is essential to understand those malware towards their detection. In this work, we look into a comparative study of android and IoT malware through the lenses of graph measures: we construct abstract structures, using the control flow graph (CFG) to represent malware binaries. Using those structures, we conduct an in-depth analysis of malicious graphs extracted from the android and IoT malware. By reversing 2,874 and 201 malware binaries corresponding to the IoT and android platforms, respectively, extract their CFGs, and analyze them across both general characteristics, such as the number of nodes and edges, as well as graph algorithmic constructs, such as average shortest path, betweenness, closeness, density, etc. Using the CFG as an abstract structure, we emphasize various interesting findings, such as the prevalence of unreachable code in android malware, noted by the multiple components in their CFGs, the high density, strong closeness and betweenness, and larger number of nodes in the android malware, compared to the IoT malware, highlighting its higher order of complexity. We note that the number of edges in android malware is larger than that in IoT malware, highlighting a richer flow structure of those malware samples, despite their structural simplicity (number of nodes). We note that most of those graph-based properties can be used as discriminative features for classification.
Publication Date
1-1-2018
Publication Title
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume
11280 LNCS
Number of Pages
259-272
Document Type
Article; Proceedings Paper
Personal Identifier
scopus
DOI Link
https://doi.org/10.1007/978-3-030-04648-4_22
Copyright Status
Unknown
Socpus ID
85059072847 (Scopus)
Source API URL
https://api.elsevier.com/content/abstract/scopus_id/85059072847
STARS Citation
Alasmary, Hisham; Anwar, Afsah; Park, Jeman; Choi, Jinchun; and Nyang, Daehun, "Graph-Based Comparison Of Iot And Android Malware" (2018). Scopus Export 2015-2019. 9537.
https://stars.library.ucf.edu/scopus2015/9537