Android Malware Detection: A Survey

ODUSAMI, M, ABAYOMI-ALLI, O, MISRA, S, SHOBAYO, Olamilekan, DAMASEVICIUS, R and MASKELIUNAS, R (2018). Android Malware Detection: A Survey. In: FLOREZ, Hector, DIAZ, Cesar and CHAVARRIAGA, Jaime, (eds.) Applied Informatics. First International Conference, ICAI 2018, Bogotá, Colombia, November 1-3, 2018, Proceedings. Communications in computer and information science, 942 (942). Cham, Switzerland, Springer International Publishing, 255-266.

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Abstract

In the world today, smartphones are evolving every day and with this evolution, security becomes a big issue. Security is an important aspect of the human existence and in a world, with inadequate security, it becomes an issue for the safety of the smartphone users. One of the biggest security threats to smartphones is the issue of malware. The study carried out a survey on malware detection techniques towards identifying gaps, and to provide the basis for improving and effective measure for unknown android malware. The results showed that machine learning is a more promising approach with higher detection accuracy. Upcoming researchers should look into deep learning approach with the use of a large dataset in order to achieve a better accuracy.

Item Type:	Book Section
Additional Information:	Series ISSN: 1865-0937
Identification Number:	https://doi.org/10.1007/978-3-030-01535-0_19
Page Range:	255-266
SWORD Depositor:	Symplectic Elements
Depositing User:	Symplectic Elements
Date Deposited:	07 Jun 2022 16:09
Last Modified:	01 Dec 2022 16:14
URI:	https://shura.shu.ac.uk/id/eprint/29801

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