TITLE:
A Survey of Cloud Computing Detection Techniques against DDoS Attacks
AUTHORS:
Sabah Alzahrani, Liang Hong
KEYWORDS:
DDoS, IDS, Signature, Anomaly, Hybrid, SVM, Neural Network, Cloud, Machine Learning, Big Data
JOURNAL NAME:
Journal of Information Security,
Vol.9 No.1,
December
21,
2017
ABSTRACT:
A Distributed Denial of Service Attack (DDoS) is an attack in which multiple systems compromised by a Trojan are maliciously used to target a single system. The attack leads to the denial of a certain service on the target system. In a DDoS attack, both the target system and the systems used to perform the attack are all victims of the attack. The compromised systems are also called Botnets. These attacks occur on networked systems, among them the cloud computing facet. Scholars have tried coming up with separate mechanisms for detecting and preventing such attacks long before they occur. However, as technology progresses in advancement so do the attack mechanisms. In cloud computing, security issues affect various stakeholders who plan on cloud adoption. DDoS attacks are such serious concerns that require mitigation in the cloud. This paper presents a survey of the various mechanisms, both traditional and modern, that are applied in detecting cloud-based DDoS attacks.