A hybrid deep learning model for detecting DDoS flooding attacks in SIP-based systems-Reference-Cited by-同舟云学术

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A hybrid deep learning model for detecting DDoS flooding attacks in SIP-based systems

Published:2024-02 Issue: Volume:240 Page:110146
ISSN:1389-1286
Container-title:Computer Networks
language:en
Short-container-title:Computer Networks

Author:

Younes Osama S.^ORCID

Publisher

Elsevier BV

Reference40 articles.

1. H.S. Rosenberg, G. Camarillo, A. Johnston, J. Peterson, R. Sparks, M. Handley, and E. Schooler, RFC 3261-Sip: session Initiation Protocol, 2002.

2. IP multimedia subsystem SIP registration signaling evaluation for mission critical communication systems;Ali,2015

3. CO-CAC: a new approach to call admission control for VoIP in 5G/WiFi UAV-based relay networks;Mayor;Comput. Commun.,2023

4. Sip Handbook Services, Technologies, and Security of Session Initiation Protocol;Ahson,2009

5. Securing VoIP: Keeping Your VoIP Network Safe;Bates,2015

Cited by 3 articles. 订阅此论文施引文献订阅此论文施引文献，注册后可以免费订阅5篇论文的施引文献，订阅后可以查看论文全部施引文献

1. DDoSNet: Detection and prediction of DDoS attacks from realistic multidimensional dataset in IoT network environment;Egyptian Informatics Journal;2024-09

2. Studying the Impact of Different TCP DoS Attacks on the Parameters of VoIP Streams;Telecom;2024-07-08

3. Smart network security using advanced ensemble-DDoS attack detection and hybrid JA-SLOA-linked optimal routing-based mitigation;Australian Journal of Electrical and Electronics Engineering;2024-04-21

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