Abstract
Cyber attacks hit companies, businesses, and common people every day. Cybercrime is increasing year by year as criminals that are trying to benefit from vulnerable sources. Software attacks are very difficult to detect as it hides in a very sophisticated way on the network. This survey paper gives a review of various machine learning (ML) methods used to detect different attacks. Several methods/architectures developed by researchers to detect cybercrimes using deep learning and machine learning techniques of classification are also discussed. It can be seen that machine learning and deep learning models are efficient in detecting cybercrimes with high accuracy when proper training is given.
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Pakhare, P.S., Krishnan, S., Charniya, N.N. (2021). A Survey on Recent Advances in Cyber Assault Detection Using Machine Learning and Deep Learning. In: Raj, J.S., Iliyasu, A.M., Bestak, R., Baig, Z.A. (eds) Innovative Data Communication Technologies and Application. Lecture Notes on Data Engineering and Communications Technologies, vol 59. Springer, Singapore. https://doi.org/10.1007/978-981-15-9651-3_47
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DOI: https://doi.org/10.1007/978-981-15-9651-3_47
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