Fast detection of distributed denial of service attacks in VoIP networks using convolutional neural networks
Joint Authors
Nazih, Walid
Hifni, Yasir
al-Kilani, Wail W.
Abd al-Qadir, Tamir
Source
International Journal of Intelligent Computing and Information Sciences
Issue
Vol. 20, Issue 2 (31 Dec. 2020), pp.125-138, 14 p.
Publisher
Ain Shams University Faculty of Computer and Information Sciences
Publication Date
2020-12-31
Country of Publication
Egypt
No. of Pages
14
Main Subjects
Information Technology and Computer Science
Topics
Abstract EN
Voice over Internet Protocol (VoIP) is a recent technology used to transfer media and voice over Internet Protocol (IP).
Many organizations moved to VoIP services instead of the traditional telephone systems because of its low cost and variety of introduced services.
The Session Initiation Protocol (SIP) is the most used protocol for signaling functions in VoIP networks.
It has simple implantation but suffers from less protection against attacks.
The Distributed Denial of Service (DDoS) attack is a dangerous attack that preventing legitimate users from using VoIP services and draining their resources.
In this paper, we proposed an approach that utilizes deep learning to detect DDoS attacks.
The proposed approach uses token embedding to improve the extracted features of SIP messages.
Then, Convolutional Neural Network (CNN) was used to detect DDoS attacks with different intensities.
Furthermore, a real VoIP dataset that contains different scenarios of attacks was used to evaluate the proposed approach.
Our experiments find that the CNN model achieved a high F1 score (99-100%) as another deep learning approach that utilizes Recurrent Neural Network (RNN) but with less detection time.
Also, it outperforms another system that depends on classical machine learning in case of low-rate DDoS attacks.
American Psychological Association (APA)
Nazih, Walid& Hifni, Yasir& al-Kilani, Wail W.& Abd al-Qadir, Tamir. 2020. Fast detection of distributed denial of service attacks in VoIP networks using convolutional neural networks. International Journal of Intelligent Computing and Information Sciences،Vol. 20, no. 2, pp.125-138.
https://search.emarefa.net/detail/BIM-1086198
Modern Language Association (MLA)
Nazih, Walid…[et al.]. Fast detection of distributed denial of service attacks in VoIP networks using convolutional neural networks. International Journal of Intelligent Computing and Information Sciences Vol. 20, no. 2 (2020), pp.125-138.
https://search.emarefa.net/detail/BIM-1086198
American Medical Association (AMA)
Nazih, Walid& Hifni, Yasir& al-Kilani, Wail W.& Abd al-Qadir, Tamir. Fast detection of distributed denial of service attacks in VoIP networks using convolutional neural networks. International Journal of Intelligent Computing and Information Sciences. 2020. Vol. 20, no. 2, pp.125-138.
https://search.emarefa.net/detail/BIM-1086198
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references : p. 136-138
Record ID
BIM-1086198