Abstract
Content Delivery Networks (CDNs) are increasingly deployed for their efficient content delivery and are often integrated with Software Defined Networks (SDNs) to achieve centrality and programmability of the network. However, these networks are also an attractive target for network attackers whose main goal is to exhaust network resources. One attack approach is to over-flood the OpenFlow switch tables containing routing information. Due to the increasing number of different flooding attacks such as DDoS, it becomes difficult to distinguish these attacks from normal traffic when evaluated with traditional attack detection methods. This paper proposes an architectural method that classifies and defends all possible forms of DDoS attack and legitimate Flash Crowd traffic using a segregated dimension functioning cognitive process based in a controller module. Our results illustrate that the proposed model yields significantly enhanced performance with minimal false positives and false negatives when classified with optimal Support Vector Machine and Logistic Regression algorithms. The traffic classifications initiate deployment of security rules to the OpenFlow switches, preventing new forms of flooding attacks. To the best of our knowledge, this is the first work conducted on SDN-driven CDNi used to detect and defend against all possible DDoS attacks through traffic segregated dimension functioning coupled with cognitive classification.
Original language | English |
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Pages (from-to) | 163-185 |
Number of pages | 23 |
Journal | Computer Science and Information Systems |
Volume | 15 |
Issue number | 1 |
DOIs | |
State | Published - Jan 2018 |
Bibliographical note
Funding Information:Acknowledgements. The work was supported by the National Research Foundation of Korea (NRF) funded by the Korea government (MSIP) (2016R1A2B4015899). Kijoon Chae is corresponding author.
Publisher Copyright:
© 2018, ComSIS Consortium. All rights reserved.
Keywords
- CDN
- CDNi
- DDoS
- Flash Crowd
- Logistic Regression
- Machine Learning
- SDN
- Support Vector Machine