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Scale Inside-Out: Rapid Mitigation of Cloud DDoS Attacks

Somani, G., Gaur, M. S., Sanghi, D. , Conti, M. & Rajarajan, M. (2017). Scale Inside-Out: Rapid Mitigation of Cloud DDoS Attacks. IEEE Transactions on Dependable and Secure Computing, 15(6), pp. 959-973. doi: 10.1109/tdsc.2017.2763160


The distributed denial of service (DDoS) attacks in cloud computing requires quick absorption of attack data. DDoS attack mitigation is usually achieved by dynamically scaling the cloud resources so as to quickly identify the onslaught features to combat the attack. The resource scaling comes with an additional cost which may prove to be a huge disruptive cost in the cases of longer, sophisticated, and repetitive attacks. In this work, we address an important problem, whether the resource scaling during attack, always result in rapid DDoS mitigation? For this purpose, we conduct real-time DDoS attack experiments to study the attack absorption and attack mitigation for various target services in the presence of dynamic cloud resource scaling. We found that the activities such as attack absorption which provide timely attack data input to attack analytics, are adversely compromised by the heavy resource usage generated by the attack. We show that the operating system level local resource contention, if reduced during attacks, can expedite the overall attack mitigation. The attack mitigation would otherwise not be completed by the dynamic scaling of resources alone. We conceived a novel relation which terms “Resource Utilization Factor” for each incoming request as the major component in forming the resource contention. To overcome these issues, we propose a new “Scale Inside-out” approach which during attacks, reduces the “Resource Utilization Factor” to a minimal value for quick absorption of the attack. The proposed approach sacrifices victim service resources and provides those resources to mitigation service in addition to other co-located services to ensure resource availability during the attack. Experimental evaluation shows up to 95 percent reduction in total attack downtime of the victim service in addition to considerable improvement in attack detection time, service reporting time, and downtime of co-located services.

Publication Type: Article
Additional Information: © 2019 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Computer crime, Cybersecurity, Cloud computing, Dynamic scheduling, Resource management, Denial-of-service attack, Computer security
Subjects: Q Science > QA Mathematics > QA75 Electronic computers. Computer science
T Technology > TA Engineering (General). Civil engineering (General)
Departments: School of Science & Technology > Engineering
SWORD Depositor:
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