Cited by 123Network Security and Intrusion DetectionWireless Networks and ProtocolsAdversarial Robustness in Machine Learning

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

Empirical Evaluation of Attacks Against IEEE 802.11 Enterprise Networks: The AWID3 Dataset

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Abstract

This work serves two key objectives. First, it markedly supplements and extends the well-known AWID corpus by capturing and studying traces of a wide variety of attacks hurled in the IEEE 802.1X Extensible Authentication Protocol (EAP) environment. Second, given that all the 802.11-oriented attacks have been carried out when the defenses introduced by Protected Management Frames (PMF) were operative, it offers the first to our knowledge full-fledged empirical study regarding the robustness of the IEEE 802.11w amendment, which is mandatory for WPA3 certified devices. Under both the aforementioned settings, the dataset, and study at hand are novel and are anticipated to be of significant aid towards designing and evaluating intrusion detection systems. Moreover, in an effort to deliver a well-rounded dataset of greater lifespan, and under the prism of an attacker escalating their assault from the wireless MAC layer to higher ones, we have additionally included several assaults that are common to IEEE 802.3 networks. Since the corpus is publicly offered in the form of raw cleartext pcap files, future research can straightforwardly exploit any subset of features, depending on the particular application scenario.

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Cited by

Metadata

Authors
Chatzoglou, E., Kambourakis, G., & Kolias, C.
Affiliations
  • University of the Aegean (GR)
  • Joint Research Centre (IT)
  • University of Idaho (US)
Venue
IEEE Access
Published
2021
Volume
9
Pages
34188-34205
ISSN
2169-3536 (ISSN-L)
OpenAlex
W3132842072
Cited by
123
References
1
Citations by year
2026: 21 · 2025: 35 · 2024: 30 · 2023: 20 · 2022: 13 · 2021: 4
FWCI
7.52
Type
journal article
Language
en
Open access
Locations
  • IEEE Access (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Topics
  • Physical Sciences › Computer Science › Computer Networks and Communications › Network Security and Intrusion Detection
  • Physical Sciences › Computer Science › Computer Networks and Communications › Wireless Networks and Protocols
  • Physical Sciences › Computer Science › Artificial Intelligence › Adversarial Robustness in Machine Learning
Keywords
IEEE 802.1X, Extensible Authentication Protocol, WPA3, wireless network security, intrusion detection systems, MAC layer attacks, attack traces

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