Survey on applications of deep learning and machine learning techniques for cyber security

被引:5
|
作者
Alghamdi M.I. [1 ]
机构
[1] Al-Baha University, Al-Baha City, Kingdom of Saudi Arabia, Al-Baha
来源
Alghamdi, Mohammed I. (mialmushilah@bu.edu.sa) | 2020年 / International Association of Online Engineering卷 / 14期
关键词
Applications; Cybersecurity; Deep learning; Machine learning;
D O I
10.3991/ijim.v14i16.16953
中图分类号
学科分类号
摘要
The research aimed to conduct an extensive study of machine learning and deep learning methods in cybersecurity. To accomplish the objectives, the research carried out a qualitative study based on secondary data collection to review the available studies and literature. The research has examined three machine learning methods and three deep learning methods to study the most popular techniques used in cybersecurity. During the research, the working mechanism of each method was studied along with their strengths and weaknesses. Also, a comparative discussion has been made to examine the most effective method for cybersecurity. Limitations in the current literature were also identified, and future direction is also given to target and develop the weak areas of machine learning and deep learning methods. © 2020 by the authors.
引用
收藏
页码:210 / 224
页数:14
相关论文
共 50 条
  • [31] ENHANCING IIOT SECURITY WITH MACHINE LEARNING AND DEEP LEARNING FOR INTRUSION DETECTION
    Awad, Omer Fawzi
    Hazim, Layth Rafea
    Jasim, Abdulrahman Ahmed
    Ata, Oguz
    MALAYSIAN JOURNAL OF COMPUTER SCIENCE, 2024, 37 (02) : 139 - 153
  • [32] Big data analytics deep learning techniques and applications: A survey
    Selmy, Hend A.
    Mohamed, Hoda K.
    Medhat, Walaa
    INFORMATION SYSTEMS, 2024, 120
  • [33] Machine learning and deep learning techniques for detecting and mitigating cyber threats in IoT-enabled smart grids: a comprehensive review
    Tirulo, Aschalew
    Chauhan, Siddhartha
    Dutta, Kamlesh
    INTERNATIONAL JOURNAL OF INFORMATION AND COMPUTER SECURITY, 2024, 24 (3-4) : 284 - 321
  • [34] A survey on advanced machine learning and deep learning techniques assisting in renewable energy generation
    Revathi, B. Sri
    ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH, 2023, 30 (41) : 93407 - 93421
  • [35] A Survey of Machine and Deep Learning Methods for Internet of Things (IoT) Security
    Al-Garadi, Mohammed Ali
    Mohamed, Amr
    Al-Ali, Abdulla Khalid
    Du, Xiaojiang
    Ali, Ihsan
    Guizani, Mohsen
    IEEE COMMUNICATIONS SURVEYS AND TUTORIALS, 2020, 22 (03): : 1646 - 1685
  • [36] Exploring the potential of deep learning and machine learning techniques for randomness analysis to enhance security on IoT
    Kenan Ince
    International Journal of Information Security, 2024, 23 : 1117 - 1130
  • [37] Machine learning and deep learning techniques for detecting malicious android applications: An empirical analysis
    Parnika Bhat
    Sunny Behal
    Kamlesh Dutta
    Proceedings of the Indian National Science Academy, 2023, 89 : 429 - 444
  • [38] Static Analysis of Information Systems for IoT Cyber Security: A Survey of Machine Learning Approaches
    Kotenko, Igor
    Izrailov, Konstantin
    Buinevich, Mikhail
    SENSORS, 2022, 22 (04)
  • [39] Machine Learning and Deep Learning in Chemical Health and Safety: A Systematic Review of Techniques and Applications
    Jiao, Zeren
    Hu, Pingfan
    Xu, Hongfei
    Wang, Qingsheng
    ACS CHEMICAL HEALTH & SAFETY, 2020, 27 (06) : 316 - 334
  • [40] Machine learning and deep learning techniques for detecting malicious android applications: An empirical analysis
    Bhat, Parnika
    Behal, Sunny
    Dutta, Kamlesh
    PROCEEDINGS OF THE INDIAN NATIONAL SCIENCE ACADEMY, 2023, 89 (03): : 429 - 444