A Model for Adaptive and Distributed Intrusion Detection for Cloud Computing

Cloud computing is becoming an increasing popular technology where clients can subscribe for resources on a pay per use basis. Distributed Denial of Service (DDoS) is a common form of attack that targets cloud computing. Also, new features of cloud computing such as virtualization and virtual machine migration introduces additional challenges to cloud security as studies reports that the detection accuracy of anomaly detection system is degraded during the migration of virtual machine from one host to another. Therefore, providing effective security is paramount to the quality of service in cloud computing. DDoS attack is carried out by compromising vulnerable host which are used to carry out coordinated attack against a target. This paper therefore proposed a model for an adaptive and distributed IDS for cloud computing capable of effectively detecting coordinated attacks and also addressing challenges introduced by migration of virtual machines in cloud IDS.

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