Cited by 280Network Security and Intrusion DetectionArtificial Immune Systems ApplicationsNetwork Packet Processing and Optimization

The DOI matches its Crossref record; 1 of the 1 references it cites were found in a registry or an index.

Toward Credible Evaluation of Anomaly-Based Intrusion-Detection Methods

Tavallaee, Mahbod, Stakhanova, Natalia, Ghorbani, Ali Akbar·2010·IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)

Abstract

Since the first introduction of anomaly-based intrusion detection to the research community in 1987, the field has grown tremendously. A variety of methods and techniques introducing new capabilities in detecting novel attacks were developed. Most of these techniques report a high detection rate of 98% at the low false alarm rate of 1%. In spite of the anomaly-based approach's appeal, the industry generally favors signature-based detection for mainstream implementation of intrusion-detection systems. While a variety of anomaly-detection techniques have been proposed, adequate comparison of these methods' strengths and limitations that can lead to potential commercial application is difficult. Since the validity of experimental research in academic computer science, in general, is questionable, it is plausible to assume that research in anomaly detection shares the above problem. The concerns about the validity of these methods may partially explain why anomaly-based intrusion-detection methods are not adopted by industry. To investigate this issue, we review the current state of the experimental practice in the area of anomaly-based intrusion detection and survey 276 studies in this area published during the period of 2000-2008. We summarize our observations and identify the common pitfalls among surveyed works.

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Crossref · 10.1109/tsmcc.2010.2048428

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  • Through taxonomic research and development, defence systems have employed techniques that analyse relationships between application behaviour and response.

    “Through taxonomic research and development, defence systems have employed techniques that analyse relationships between application behaviour and response (sandboxing [Blasing et al. 2010; Greamo and A.Ghosh 2011], dynamic anomaly based scanning [Tavallaee et al. 2010] etc.).”

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Research works printed but not linked: 27

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Metadata

Authors
Tavallaee, M., Stakhanova, N., & Ghorbani, A. A.
Affiliations
University of New Brunswick (CA)
Venue
IEEE Transactions on Systems, Man, and Cybernetics, Part C (Applications and Reviews)
Published
2010-09
Volume
40
Issue
5
Pages
516-524
ISSN
  • 1094-6977 (ISSN-L)
  • 1558-2442
OpenAlex
W2103414007
Cited by
280
References
1
Citations by year
2026: 11 · 2025: 11 · 2024: 23 · 2023: 21 · 2022: 34 · 2021: 28 · 2020: 28 · 2019: 22 · 2018: 14 · 2017: 10 · 2016: 14 · 2015: 14 · 2014: 19 · 2013: 9 · 2012: 16
FWCI
13.77
Type
journal article
Language
en
Open access
closed
Locations
IEEE Transactions on Systems Man and Cybernetics Part C (Applications and Reviews) (publishedVersion)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
  • Physical Sciences › Computer Science › Artificial Intelligence › Artificial Immune Systems Applications
  • Physical Sciences › Computer Science › Hardware and Architecture › Network Packet Processing and Optimization
Keywords
anomaly-based intrusion detection, intrusion detection evaluation, experimental validity, novel attack detection, signature-based detection

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