MOCDroid: multi-objective evolutionary classifier for Android malware detection

Martín, Alejandro, Menéndez, Héctor D. ORCID: https://orcid.org/0000-0002-6314-3725 and Camacho, David ORCID: https://orcid.org/0000-0002-5051-3475 (2017) MOCDroid: multi-objective evolutionary classifier for Android malware detection. Soft Computing, 21 (24) . pp. 7405-7415. ISSN 1432-7643 [Article] (doi:10.1007/s00500-016-2283-y)

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Abstract

Malware threats are growing, while at the same time, concealment strategies are being used to make them undetectable for current commercial Anti-Virus. Android is one of the target architectures where these problems are specially alarming, due to the wide extension of the platform in different everyday devices.The detection is specially relevant for Android markets in order to ensure that all the software they offer is clean, however, obfuscation has proven to be effective at evading the detection process. In this paper we leverage third-party calls to bypass the effects of these concealment strategies, since they cannot be obfuscated. We combine clustering and multi-objective optimisation to generate a classifier based on specific behaviours defined by 3rd party calls groups. The optimiser ensures that these groups are related to malicious or benign behaviours cleaning any non-discriminative pattern. This tool, named MOCDroid, achieves an ac-curacy of 94.6% in test with 2.12% of false positives with real apps extracted from the wild, overcoming all commercial Anti-Virus engines from VirusTotal.

Item Type: Article
Keywords (uncontrolled): Android, malware, clustering, classification
Research Areas: A. > Business School > International Management and Innovation
A. > Business School > International Management and Innovation > Corporate Social Responsibility and Business Ethics group
A. > Business School > International Management and Innovation > International Business group
Item ID: 28801
Notes on copyright: This is a post-peer-review, pre-copyedit version of an article published in Soft Computing. The final authenticated version is available online at: http://dx.doi.org/10.1007/s00500-016-2283-y
Useful Links:
Depositing User: Hector Menendez Benito
Date Deposited: 02 Feb 2020 21:12
Last Modified: 08 Feb 2021 20:10
URI: https://eprints.mdx.ac.uk/id/eprint/28801

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