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Cloud security is one among most vital problems that have attracted lots of analysis and development effort in past few years. Notably, attackers will explore vulnerabilities of a cloud system and compromise virtual machines to deploy any large-scale Distributed Denial-of-Service (DDoS). DDoS attacks typically involve early stage actions like multi-step exploitation, low frequency vulnerability scanning, and compromising known vulnerable virtual machines as zombies, and at last DDoS attacks through the compromised zombies. Inside the cloud system, particularly the Infrastructure-as-a-Service (IaaS) clouds, the detection of zombie exploration attacks is very troublesome. this can be as a result of cloud users could install vulnerable applications on their virtual machines. to forestall vulnerable virtual machines from being compromised within the cloud, we have a tendency to propose a multi-phase distributed vulnerability detection, measuring, and measure choice mechanism known as NICE, that is made on attack graph primarily based analytical models and reconfigurable virtual network-based countermeasures. The projected framework leverages Open Flow schedule arthropod genus to create a monitor and management plane over distributed programmable virtual switches so as to considerably improve attack detection and mitigate attack consequences. The system and security evaluations demonstrate the potency and effectiveness of the projected resolution.

NETWORK INTRUSION DETECTION AND MEASURE CHOICE IN VIRTUAL NETWORK SYSTEMS-NICE