DOI: 10.55524/ijirem.2022.9.3.6 | DOI URL: https://doi.org/10.55524/ijirem.2022.9.3.6 Crossref
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Praveen Hugar , Mayur Pershad, T. Sathvika, Ganesh Bhukya
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.
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Assistant Professor, Department of Information Technology, J B Institute of Engineering and Technology, Moinabad, India
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