Identifying ATT&CK Tactics in Android Malware Control Flow Graph through Graph Representation Learning and Interpretability (Student Abstract)
Document Type
Conference Proceeding
Publication Date
6-30-2022
Abstract
To mitigate a malware threat it is important to understand the malware's behavior. The MITRE ATT&ACK 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 provides an automation methodology to locate TTP in a sub-part of the control flow graph that describes the execution flow of a malware executable. This methodology merges graph representation learning and tools for machine learning explanation.
Identifier
85147602946 (Scopus)
ISBN
[1577358767, 9781577358763]
Publication Title
Proceedings of the 36th Aaai Conference on Artificial Intelligence Aaai 2022
External Full Text Location
https://doi.org/10.1609/aaai.v36i11.21607
First Page
12941
Last Page
12942
Volume
36
Grant
22-001
Fund Ref
National Science Foundation
Recommended Citation
Fairbanks, Jeffrey; Orbe, Andres; Patterson, Christine; Serra, Edoardo; and Scheepers, Marion, "Identifying ATT&CK Tactics in Android Malware Control Flow Graph through Graph Representation Learning and Interpretability (Student Abstract)" (2022). Faculty Publications. 2872.
https://digitalcommons.njit.edu/fac_pubs/2872