Identifying ATTCK Tactics in Android Malware Control Flow Graph Through Graph Representation Learning and Interpretability
Document Type
Conference Proceeding
Publication Date
1-1-2021
Abstract
To mitigate a malware threat it is important to understand the malware's behavior. The MITRE ATTACK ontology specifies an enumeration of tactics, techniques, and procedures (TTP) that characterize malware. However, absent are automated procedures that would characterize, given the malware executable, which part of the execution flow is connected with a specific TTP. This paper is the first in providing an automation methodology to locate TTP in a sub-part of the control flow graph that describes the execution flow of a mal-ware executable. This methodology merges graph representation learning and tools for machine learning explanation.
Identifier
85125360808 (Scopus)
ISBN
[9781665439022]
Publication Title
Proceedings 2021 IEEE International Conference on Big Data Big Data 2021
External Full Text Location
https://doi.org/10.1109/BigData52589.2021.9671343
First Page
5602
Last Page
5608
Grant
22-001
Fund Ref
National Science Foundation
Recommended Citation
Fairbanks, Jeffrey; Orbe, Andres; Patterson, Christine; Layne, Janet; Serra, Edoardo; and Scheepers, Marion, "Identifying ATTCK Tactics in Android Malware Control Flow Graph Through Graph Representation Learning and Interpretability" (2021). Faculty Publications. 4652.
https://digitalcommons.njit.edu/fac_pubs/4652
