Autors: Ivanova, V., Tashev, T. A., Draganov, I. R.
Title: DDoS Attacks Classification using SVM
Keywords: Distributed denial of service, Internet of things, Kernel fu

References

    Issue

    WSEAS Transactions on Information Science and Applications, vol. 19, pp. 1-11, 2022, United States, WSEAS, DOI 10.37394/23209.2022.19.1

    Copyright WSEAS

    Цитирания (Citation/s):
    1. Bibi S., Zulkifli N., Safdar G.A., Iqbal S., Support Vector Machine (SVM) based Detection for Volumetric Bandwidth Distributed Denial of Service (DVB-DDOS) Attack within Gigabit Passive Optical Network, 2025, Sinergi (Indonesia), issue 1, vol. 29, pp. 185-196, DOI 10.22441/sinergi.2025.1.017, issn 14102331, eissn 24601217 - 2025 - в издания, индексирани в Scopus
    2. Li Y., Deng X., Yang A., Gao J., A Transformer-Based Framework for DDoS Attack Detection via Temporal Dependency and Behavioral Pattern Modeling, 2025, Algorithms, issue 10, vol. 18, DOI 10.3390/a18100628, eissn 19994893 - 2025 - в издания, индексирани в Scopus
    3. Hassan Z., Ghali A.A., Guan G.H., Lee G.M., DoS/DDoS Threat Classification in IoT Health Wearables Using Naïve Bayes, 2025, 2025 6th International Conference on Artificial Intelligence and Data Sciences from Insights to Impact Leveraging AI and Data Science for Strategic Decisions Aidas 2025 Conference Proceedings, issue 0, pp. 36-43, DOI 10.1109/AiDAS67696.2025.11213635 - 2025 - в издания, индексирани в Scopus

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