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Deep learning algorithms for cyber security applications: A survey

journal contribution
posted on 2021-01-01, 00:00 authored by Guangjun Li, P Sharma, Lei PanLei Pan, Sutharshan RajasegararSutharshan Rajasegarar, Chandan KarmakarChandan Karmakar, Nick Patterson
With the development of information technology, thousands of devices are connected to the Internet, various types of data are accessed and transmitted through the network, which pose huge security threats while bringing convenience to people. 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.

History

Journal

Journal of Computer Security

Volume

29

Issue

5

Pagination

447 - 471

Publisher

IOS PRESS

ISSN

0926-227X

eISSN

1875-8924

Language

English

Publication classification

C1 Refereed article in a scholarly journal