Autors: Ivanova, V., Tashev, T. A., Draganov, I. R.
Title: Random Forest Detector and Classifier of Multiple IoT-based DDoS Attacks
Keywords: classifier, DDoS, detector, IoT, malicious traffic, network,

References

    Issue

    WSEAS Transactions on Information Science and Applications, vol. 19, pp. 30-43, 2022, Greece, WSEAS, DOI 10.37394/23209.2022.19.4

    Copyright WSEAS

    Цитирания (Citation/s):
    1. Sawah M.S., Elmannai H., El-Bary A.A., Lotfy K., Sheta O.E., Distributed denial of service (DDoS) classification based on random forest model with backward elimination algorithm and grid search algorithm, 2025, Scientific Reports, issue 1, vol. 15, DOI 10.1038/s41598-025-03868-x, eissn 20452322 - 2025 - в издания, индексирани в Scopus
    2. Sharif, D. M. (2023, October). Application-layer DDoS detection via efficient machine learning and feature selection. In 2023 International Conference on Engineering Applied and Nano Sciences (ICEANS) (pp. 19-23). IEEE. - 2023 - в издания, индексирани в Scopus и/или Web of Science
    3. Ismanto E., Cynthia E.P., Enhanced Internet of Things Security Via CNN and LSTM-Based Attack Detection Systems, 2026, Studies in Computational Intelligence, issue 0, vol. 1232, pp. 89-101, DOI 10.1007/978-3-032-04174-6_10, issn 1860949X, eissn 18609503 - 2026 - в издания, индексирани в Scopus

    Вид: статия в списание, публикация в издание с импакт фактор, публикация в реферирано издание, индексирана в Scopus