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- W4285014716 abstract "Abstract Cloud computing technology created a revolution in IT Industry that provides on-demand resources, flexibility, scalability, and lower maintenance to infrastructure costs. Distributed Denial of Service (DDoS) attack blocks the services by flooding high or low volume of malicious traffic to exhaust the servers, resources, etc of cloud. In today’s era, they are even difficult to detect because of low rate traffic and its hidden approach in cloud. The study of all DDoS attack with their possible solution is essential to protect cloud computing environment. In this paper, we have proposed a Fuzzy Q Learning algorithm and Chebyshev’s Inequality principle to counter the problem of DDoS attacks. The Proposed framework follows the inclusion of Chebyshew’s inequality for work load prediction in cloud in the analysis phase and fuzzy QLearning in planning phase .Experimental results proves that in our proposed FQBDDA model, prevent DDoS attack." @default.
- W4285014716 created "2022-07-12" @default.
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- W4285014716 date "2022-07-11" @default.
- W4285014716 modified "2023-10-16" @default.
- W4285014716 title "Prevention of DDoS Attack in Cloud Computing using Fuzzy Q – Learning Algorithm" @default.
- W4285014716 doi "https://doi.org/10.21203/rs.3.rs-1536879/v1" @default.
- W4285014716 hasPublicationYear "2022" @default.
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