Detection of DDoS Attacks in OpenStack-based Private Cloud Using Apache Spark

• Autorzy: Gumaste Shweta , G. Narayan D. , Shinde Sumedha , K. Amit

Identyfikatory

DOI

10.26636/jtit.2020.146120

• Języki publikacji: EN

Abstrakty

EN

Security is a critical concern for cloud service providers. Distributed denial of service (DDoS) attacks are the most frequent of all cloud security threats, and the consequences of damage caused by DDoS are very serious. Thus, the design of an efficient DDoS detection system plays an important role in monitoring suspicious activity in the cloud. Real-time detection mechanisms operating in cloud environments and relying on machine learning algorithms and distributed processing are an important research issue. In this work, we propose a real-time detection of DDoS attacks using machine learning classifiers on a distributed processing platform. We evaluate the DDoS detection mechanism in an OpenStack-based cloud testbed using the Apache Spark framework. We compare the classification performance using benchmark and real-time cloud datasets. Results of the experiments reveal that the random forest method offers better classifier accuracy. Furthermore, we demonstrate the effectiveness of the proposed distributed approach in terms of training and detection time.

Słowa kluczowe

EN

cloud; DDoS; distributed processing; OpenStack; Apache Spark; random forest

• Wydawca: Instytut Łączności - Państwowy Instytut Badawczy
• Czasopismo: Journal of Telecommunications and Information Technology
• Rocznik: 2020
• Tom: nr 4
• Strony: 62--71
• Opis fizyczny: Bibliogr. 21 poz., rys., tab.

Twórcy

autor

Gumaste Shweta

• School of Computer Science and Engineering, KLE Technological University, Hubballi, Karnataka, India

autor

G. Narayan D.

• School of Computer Science and Engineering, KLE Technological University, Hubballi, Karnataka, India

autor

Shinde Sumedha

• School of Computer Science and Engineering, KLE Technological University, Hubballi, Karnataka, India

autor

K. Amit

• School of Computer Science and Engineering, KLE Technological University, Hubballi, Karnataka, India

Bibliografia

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Uwagi

Opracowanie rekordu ze środków MNiSW, umowa Nr 461252 w ramach programu "Społeczna odpowiedzialność nauki" - moduł: Popularyzacja nauki i promocja sportu (2021).