DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACK DETECTION IN CLOUD ENVIRONMENTS USING MACHINE LEARNING ALGORITHMS

Sathish Polu; Dr.V.Bapuji

DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACK DETECTION IN CLOUD ENVIRONMENTS USING MACHINE LEARNING ALGORITHMS

Authors: Sathish Polu, Dr.V.Bapuji

Unique Paper ID: 162066
Volume: 9
Issue: 7
PageNo: 927-934

Keywords: No Keywords Found

Abstract:
As cloud computing becomes an integral component of modern information technology infrastructures, the vulnerability of cloud environments to Distributed Denial of Service (DDoS) attacks poses a significant threat to the availability and performance of cloud-hosted services. This research addresses the imperative need for effective DDoS attack detection in cloud environments by leveraging machine learning algorithms. Through a comprehensive exploration of the existing literature, this study synthesizes knowledge on DDoS attack characteristics, the unique challenges posed by cloud environments, and the role of machine learning in enhancing cybersecurity. The research concludes by summarizing key findings and emphasizing the contributions to the field. Ultimately, this study underscores the critical role of machine learning in fortifying cloud security against DDoS attacks, offering a foundation for further advancements in cloud cybersecurity.

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Cite This Article

ISSN: 2349-6002
Volume: 9
Issue: 7
PageNo: 927-934

DISTRIBUTED DENIAL OF SERVICE (DDOS) ATTACK DETECTION IN CLOUD ENVIRONMENTS USING MACHINE LEARNING ALGORITHMS

Available:https://ijirt.org/Article?manuscript=162066

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Impact Factor
8.01 (Year 2024)

UGC Approved
Journal no 47859

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