International Journal of Communication Networks and Information Security (IJCNIS) · 2022 · 32 citations · 17 references
ComputingCloud ComputingComputer ScienceCloud SecurityComputer SecurityNetwork SecurityCloud Traffic EngineeringDenial-of-service AttacksIntrusion DetectionAttack MitigationDdos DetectionDenial Of ServiceDenial Of Service Attack MitigationDenial-of-service DetectionDenial-of-service MitigationDistributed Denial Of ServiceFlooding
Distributed Denial of Service (DDoS) attack launched in Cloud computing environment resulted in loss of sensitive information, Data corruption and even rarely lead to service shutdown. Entropy based DDoS mitigation approach analyzes the heuristic data and acts dynamically according to the traffic behavior to effectively segregate the characteristics of incoming traffic. Heuristic data helps in detecting the traffic condition to mitigate the flooding attack. Then, the traffic data is analyzed to distinguish legitimate and attack characteristics. An additional Trust mechanism has been deployed to differentiate legitimate and aggressive legitimate users. Hence, Goodput of Datacenter has been improved by detecting and mitigating the incoming traffic threats at each stage. Simulation results proved that the Enhanced Entropy approach behaves better at DDoS attack prone zones. Profit analysis also proved that the proposed mechanism is deployable at Datacenter for attack mitigation and resource protection which eventually results in beneficial service at slenderized revenue
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Flash crowds and denial of service attacks
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A fuzzy pattern-based filtering algorithm for botnet detection
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