Computer Applications and Software, Volume. 42, Issue 4, 340(2025)

RESEARCH AND IMPLEMENTATION OF IOT BOTNET DETECTION MODEL BASED ON RF-RFECV AND LIGHTGBM

Hu Jinning1,2 and Mo Xiuliang1,2
Author Affiliations
  • 1School of Computer Science and Engineering, Tianjin University of Technology, Tianjin 300384, China
  • 2Tianjin Key Laboratory of Intelligent Computing and New Software Technology, Tianjin 300384, China
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    References(10)

    [1] [1] Angrishi K. Turning Internet of Things (IoT) into internet of vulnerabilities (IoV): IoT Botnets[EB]. arXiv: 1702.03681, 2017.

    [2] [2] Sinanovic H, Mrdovic S M. Analysis of Mirai malicious software[C]//25th International Conference on Software, Telecommunications and Computer Networks, 2017: 1-5.

    [5] [5] Zhao D, Traore I, Ghorbani A, et al. Peer topeer botnet detection based on flow intervals[C]//IFIP International Information Security Conference, 2012: 87-102.

    [6] [6] McDermott C D, Petrovski A V, Majdani F. Towards situational awareness of botnet activity in the internet of things[C]//International Conference on Cyber Situational Awareness, 2018: 1-8.

    [7] [7] Stevanovic M, Pedersen J M. An efficient flow-based botnet detection using supervised machine learning[C]//International Conference on Computing, Networking and Communications, 2014: 797-801.

    [10] [10] Breiman L. Manual on setting up, using, and understanding random forests V3.1[EB/OL]. [2021-08-28]. http://oz.be-rkeley.edu/users/breiman/Using_random_forest.

    [11] [11] Shang Q, Feng L, Gao S. Ahybrid method for traffic incident detection using random forest-recursive feature elimination and long short-term memory network with Bayesian optimization algorithm[J]. IEEE Access, 2020, 9: 1219-1232.

    [12] [12] Machado M R, Karray S, Sousa I T. LightGBM: An effective decision tree gradient boosting method to predict customer loyalty in the finance industry[C]//14th International Conference on Computer Science & Education, 2019: 1111-1116.

    [14] [14] Lashkari A H, Gil G D, Mamun M, et al. Characterization of Tor traffic using time based features[C]//International Conference on Information Systems Security & Privacy, 2017.

    [15] [15] Lashkari A H, Draper-Gil G, Mamun M, et al. Characterization of encrypted and VPN traffic using timer-elated features[C]//International Conference on Information Systems Security and Privacy, 2016.

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    Hu Jinning, Mo Xiuliang. RESEARCH AND IMPLEMENTATION OF IOT BOTNET DETECTION MODEL BASED ON RF-RFECV AND LIGHTGBM[J]. Computer Applications and Software, 2025, 42(4): 340

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    Paper Information

    Category:

    Received: Sep. 28, 2021

    Accepted: Aug. 25, 2025

    Published Online: Aug. 25, 2025

    The Author Email:

    DOI:10.3969/j.issn.1000-386x.2025.04.048

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