Machine Learning and Deep Learning Techniques for Cybersecurity: A Review
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-030-44289-7_5
Reference53 articles.
1. Buczak, A.L., Guven, E.: A survey of data mining and machine learning methods for cyber security intrusion detection. IEEE Commun. Surv. Tutor. 18(2), 1153–1176 (2015)
2. Mukkamala, S., Sung, A., Abraham, A.: Cyber security challenges: designing efficient intrusion detection systems and antivirus tools. In: Vemuri, V.R. (ed.) Enhancing Computer Security with Smart Technology 2006, pp. 125–163 (2005)
3. Yavanoglu, O., Aydos, M.: A review on cyber security datasets for machine learning algorithms. In: 2017 IEEE International Conference on Big Data (Big Data), pp. 2186–2193 (2017)
4. da Costa, K.A.P., Papa, J.P., Lisboa, C.O., Munoz, R., de Albuquerque, V.H.C.: Internet of Things: a survey on machine learning-based intrusion detection approaches. Comput. Netw. 151, 147–157 (2019)
5. Liu, Q., Li, P., Zhao, W., Cai, W., Yu, S., Leung, V.C.M.: A survey on security threats and defensive techniques of machine learning: a data driven view. IEEE Access 6, 12103–12117 (2018)
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