A Convolutional Neural Network for Improved Anomaly-Based Network Intrusion Detection-Reference-Cited by-同舟云学术

A Convolutional Neural Network for Improved Anomaly-Based Network Intrusion Detection

Published:2021-06-01 Issue:3 Volume:9 Page:233-252
ISSN:2167-6461
Container-title:Big Data
language:en
Short-container-title:Big Data

Author:

Al-Turaiki Isra¹^ORCID,Altwaijry Najwa²

Affiliation:

1. Department of Information Technology and College of Computer and Information Sciences, King Saud University, Riyadh Saudi Arabia.

2. Department of Computer Science, College of Computer and Information Sciences, King Saud University, Riyadh Saudi Arabia.

Publisher

Mary Ann Liebert Inc

Subject

Information Systems and Management,Computer Science Applications,Information Systems

Link

https://www.liebertpub.com/doi/pdf/10.1089/big.2020.0263

Reference54 articles.

1. 1. Kim K, Aminanto ME. Deep learning in intrusion detection perspective: Overview and further challenges. In: 2017 International Workshop on Big Data and Information Security (IWBIS), Jakarta, Indonesia: IEEE, 2017. pp. 5–10.

2. Anomaly-based network intrusion detection: Techniques, systems and challenges

3. 3. Aminanto E, Kim K. Deep learning in intrusion detection system: An overview. In: 2016 International Research Conference on Engineering and Technology (2016 IRCET), Bali, Indonesia: Higher Education Forum, 2016.

4. Machine Learning and Deep Learning Methods for Intrusion Detection Systems: A Survey

5. Deep Learning Approach for Intelligent Intrusion Detection System

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