Analysis of Methods for Detecting Malicious Software by Means of Neural Networks in Android Operating Systems

Student: Egorov Maksim

Faculty: HSE Tikhonov Moscow Institute of Electronics and Mathematics (MIEM HSE)

Educational Programme: Information Security (Bachelor)

Final Grade: 8

Year of Graduation: 2024

This paper aims to study and analyze the problem of detecting malicious software in Android operating systems. Neural models have been proposed as a solution. In the course of the work, the existed implementations were analyzed and the database, which was used in subsequent testing of models in various configurations, was compiled. During the audit, it was found out that the current neural models are able to find malware and that their effectiveness is directly affected by the number of training iterations and the completeness of the studied features.

Full text (added May 12, 2024)

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