Feature Selection of Denial-of-Service Attacks Using Entropy and Granular Computing
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The review adopted a systematic literature review approach.
“To collect and evaluate relevant information on the topic, a systematic literature review approach is adopted [122].”
From Comparative Analysis of Intrusion Detection Systems and Machine Learning Based Model Analysis through Decision Tree (2023) · cites this paper as [122]
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- Authors
- Khan, S., Gani, A., Wahab, A. W. A., & Singh, P. K.
- Affiliations
- Monash University Malaysia (MY)
- University of Malaya (MY)
- Amity University (IN)
- Corresponding author
- Khan, Suleman
- Venue
- Arabian Journal for Science and Engineering
- Published
- 2017-06-17
- Volume
- 43
- Issue
- 2
- Pages
- 499-508
- ISSN
- 1319-8025 (ISSN-L)
- 2193-567X
- 2191-4281
- OpenAlex
- W2625830901
- Cited by
- 53
- References
- 38
- Citations by year
- 2024: 3 · 2023: 8 · 2022: 4 · 2021: 9 · 2020: 6 · 2019: 12 · 2018: 8 · 2017: 3
- FWCI
- 5.28
- Type
- journal article
- Language
- en
- Open access
- closed
- Locations
- Arabian Journal for Science and Engineering (publishedVersion)
- The University of Malaya Research Repository (University of Malaya) (submittedVersion)
- Northumbria Research Link (Northumbria University) (submittedVersion)
- Topics
- Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
- Physical Sciences › Computer Science › Hardware and Architecture › Network Packet Processing and Optimization
- Physical Sciences › Engineering › Biomedical Engineering › Artificial Immune Systems Applications
- Keywords
- denial-of-service attacks, feature selection, granular computing, intrusion detection, NSL-KDD dataset, network security, attack detection
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