A Review of Intrusion Detection Systems Using Machine Learning: Attacks, Algorithms and Challenges-Reference-Cited by-同舟云学术

A Review of Intrusion Detection Systems Using Machine Learning: Attacks, Algorithms and Challenges

Published:2023 Issue: Volume: Page:59-78
ISSN:2367-3370
Container-title:Lecture Notes in Networks and Systems
language:
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Author:

Gutierrez-Garcia Jose Luis,Sanchez-DelaCruz Eddy,Pozos-Parra Maria del Pilar

Publisher

Springer Nature Switzerland

Link

https://link.springer.com/content/pdf/10.1007/978-3-031-28073-3_5

Reference46 articles.

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3. World Economic Forum. The Global Risks Report 2020. Insight Report, pp. 1–114 (2020). 978-1-944835-15-6. http://wef.ch/risks2019

4. Ponemon Institute. 2015 Cost of Data Breach Study: Impact of Business Continuity Management (2018). https://www.ibm.com/downloads/cas/AEJYBPWA

5. Katsumi, N.: Global Threat Intelligence Report Note from our CEO. NTT Security (2019)

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2. Internet of Things (IoT) Technologies With Intrusion Detection Systems in Deep Learning;Advances in Information Security, Privacy, and Ethics;2024-06-28

3. Intrusion Detection System Using Machine Learning by RNN Method;E3S Web of Conferences;2024

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