IJIREM

Abstract

Malware is any programme that gains access to or instals itself on a computer without the permission of the system's administrators. For cyber-criminals to achieve their nefarious objectives and purposes, a variety of viruses has been widely deployed. To tackle the growing number of malicious programmes and lessen their hazard, a novel deep learning framework is developed that employs NLP approaches as a starting point and combines CNN and LSTM neurones to record locally spatial correlations and learn from sequential longterm dependencies. As a result, for the malware classification job, high-level abstractions and representations are automatically derived. The accuracy of categorization rises from 0.81 (best by Random Forest) to about 1.0.

Keywords

Machine Learning, Computer Security, Malware Recognition.

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Cites this article as

[Praveen Hugar, Mayur Pershad, T. Sathvika, Ganesh Bhukya (2022), Malware Recognition Using Machine Learning Methods Based on Semantic Behaviors, International Journal of Innovative Research in Engineering & Management (IJIREM), Vol-9, Issue-3, Page No-41-44], (ISSN 2347 - 5552). www.ijirem.org