Detection and prediction of DDoS cyber attacks using spline functions-Reference-Cited by-同舟云学术

Detection and prediction of DDoS cyber attacks using spline functions

Published:2022-02-22 Issue: Volume: Page:
ISSN:
Container-title:2022 IEEE 16th International Conference on Advanced Trends in Radioelectronics, Telecommunications and Computer Engineering (TCSET)
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Author:

Kivalov Serhii¹^ORCID,Strelkovskaya Irina²^ORCID

Affiliation:

1. President of the International Humanities University International Humanities University,Odesa,Ukraine

2. Software Engineering and Computer Science International Humanities University,Faculty of Cybersecurity,Odesa,Ukraine

Publisher

IEEE

Link

http://xplorestaging.ieee.org/ielx7/9766439/9766835/09766940.pdf?arnumber=9766940

Reference22 articles.

1. Efficient Detection of DDoS Attacks Using a Hybrid Deep Learning Model with Improved Feature Selection

2. DETECTION OF DOS ATTACKS IN NETWORK TRAFFIC BY WAVELET TRANSFORM

3. Analysis of Anomaly Detection and Identification Methods in 5G Traffic

4. Cyber Resilience and Fault Tolerance of Artificial Intelligence Systems: EU Standards, Guidelines, and Reports. Proceedings of the Selected Papers on Cybersecurity Providing in Information and Telecommunication Systems (CPITS 2020);lemeshko;Kyiv Ukraine CEUR,2020

5. Design and Research of the Model for Secure Traffic Engineering Fast ReRoute under Traffic Policing Approach

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