Abstract
Extrusion of personal or sensitive data by malicious software is causing a great damage to the world. This is a very critical issue for individuals as well as various sectors of the society at large. Hundreds and thousands of cyber attackers’ cross-swords for computer systems by dropping a bombshell of malware with an intention to rift crucial data. That is why, securing this data is an important issue for the researchers. This paper focuses on developing an application which can distinguish a malicious and legitimate file with the help of machine learning algorithms.
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Mohammed, A.R., Sai Viswanath, G., Sai babu, K., Anuradha, T. (2020). Malware Detection in Executable Files Using Machine Learning. In: Satapathy, S.C., Raju, K.S., Shyamala, K., Krishna, D.R., Favorskaya, M.N. (eds) Advances in Decision Sciences, Image Processing, Security and Computer Vision. ICETE 2019. Learning and Analytics in Intelligent Systems, vol 3. Springer, Cham. https://doi.org/10.1007/978-3-030-24322-7_36
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DOI: https://doi.org/10.1007/978-3-030-24322-7_36
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