With an increase in the number of internet users, the number of cyber-attacks happening in organizations is increasing day by day. Most of the cyber-attacks involve the use of malicious software known as malware to steal personal information, gain unauthorized access to the computer systems and carry out malicious activities which can cause huge financial losses to the organizations. Viruses, worms, rootkits, adware or anything that performs malicious activities is classified as malware. Detecting malware is a major challenge faced by the anti-malware industry as the signature-based malware detection methods may not provide accurate detection of malware. In this paper, an artificial neural network approach for malware detection is presented to overcome the shortcomings of signature-based malware detection methods. The proposed method can be used as a base model for the malware detection process and can be further developed to enhance the functionality.
CITATION STYLE
Sethia, V., Kataria, S., & A, J. (2020). Malware Detection using ANN Malviz.AI. International Journal of Engineering and Advanced Technology, 9(4), 2418–2423. https://doi.org/10.35940/ijeat.d8025.049420
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