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In order to deal with security issues, many effective solutions have been given based on traditional machine learning. However, due to the characteristics of big data in cyber security, there exists a bottleneck for methods of traditional machine learning in improving security. Owning to the advantages of processing big data and high-dimensional data, new solutions for cyber security are provided based on deep learning. In this paper, the applications of deep learning are classified, analyzed and summarized in the field of cyber security, and the applications are compared between deep learning and traditional machine learning in the security field. The challenges and problems faced by deep learning in cyber security are analyzed and presented. The findings illustrate that deep learning has a better effect on some aspects of cyber security and should be considered as the first option.<\/jats:p>","DOI":"10.3233\/jcs-200095","type":"journal-article","created":{"date-parts":[[2021,6,18]],"date-time":"2021-06-18T14:47:50Z","timestamp":1624027670000},"page":"447-471","update-policy":"https:\/\/doi.org\/10.1177\/sage-journals-update-policy","source":"Crossref","is-referenced-by-count":17,"title":["Deep learning algorithms for cyber security applications: A survey"],"prefix":"10.1177","volume":"29","author":[{"given":"Guangjun","family":"Li","sequence":"first","affiliation":[{"name":"College of Sports Engineering & Information Technology, Wuhan Sports University, Wuhan, Hubei 430079, China. E-mail:\u00a0"},{"name":"School of Information Technology, Deakin University, Geelong, VIC 3220, Australia. 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