Collaborative 'many to many' DDoS detection in cloud
Publication Type
Journal Article
Publication Date
1-2016
Abstract
Cloud computing provides a scalable and cost-effective environment for users to store and process data through the internet. However, it also causes distributed denial-of-service (DDoS) attacks. DDoS attacks risk systems outage and intend to disable the service to legitimate users. In this paper, due to the nature of its large-scale and coordinated attacks, we propose a collaborative prediction approach for detecting DDoS. Our approach provides a clean and direct solution to attack defense. The DDoS attacks follow certain patterns when employing a large number of compromised machines to request for service from the servers in the victim system. So we construct an attackerserver utility matrix by the number of packets and adopt matrix factorisation to detect potential attackers collaboratively.We derive the latent attacker vectors and latent server vectors to predict the unknown entries in the matrix. Experimental results on the NS-2 simulation networks demonstrate the superiority of our approach.
Keywords
cloud computing, collaborative detection, DDoS detection, matrix factorisation
Discipline
Information Security | Software Engineering
Research Areas
Software and Cyber-Physical Systems
Publication
International Journal of Ad Hoc and Ubiquitous Computing
Volume
23
Issue
3-4
First Page
192
Last Page
202
ISSN
1743-8225
Identifier
10.1504/IJAHUC.2016.10000397
Publisher
Inderscience
Citation
MA, Siqi; David LO; and XI, Ning.
Collaborative 'many to many' DDoS detection in cloud. (2016). International Journal of Ad Hoc and Ubiquitous Computing. 23, (3-4), 192-202.
Available at: https://ink.library.smu.edu.sg/sis_research/3611
Additional URL
https://doi.org/10.1504/IJAHUC.2016.079269