Cited by 192Network Security and Intrusion DetectionNetwork Packet Processing and OptimizationInternet of Things and AI

A lightweight supervised intrusion detection mechanism for IoT networks

Open access
Roy, Souradip, Li, Juan, Choi, Bong-Jin, Bai, Yan·2022·Future Generation Computer Systems

Integrity signals

Registry

Crossref · 10.1016/j.future.2021.09.027

Cites

40 of 40 references verified0 citation errors · 0 not checkable

Statistics

Recomputing p-values needs the paper’s full text.

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Cites

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Authors
Roy, S., Li, J., Choi, B.-J., & Bai, Y.
Affiliations
  • North Dakota State University (US)
  • University of Washington Tacoma (US)
Corresponding author
Li, Juan
Venue
Future Generation Computer Systems
Publisher
Elsevier BV
Published
2022-02
Volume
127
Pages
276-285
ISSN
0167-739X (ISSN-L)
OpenAlex
W3202083238
Cited by
192
References
40
Citations by year
2026: 24 · 2025: 51 · 2024: 58 · 2023: 38 · 2022: 19 · 2021: 2
FWCI
13.12
Type
journal article
Language
en
Open access
Locations
Future Generation Computer Systems (acceptedVersion)
Funders
  • National Science Foundation (1722913, 1921576)
  • NSF
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 › Computer Science › Information Systems › Internet of Things and AI
Keywords
intrusion detection, Internet of Things security, lightweight intrusion detection, resource-constrained devices, cyberattack detection, anomaly detection, sampling, dimensionality reduction, feature selection, CICIDS2017, NSL-KDD dataset, false alarm rate

About these checks

Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.

Statistics and arithmetic are recomputed, not judged.

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