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Attack Detection in Cloud Networks Based on Artificial Intelligence Approaches

Attack Detection in Cloud Networks Based on Artificial Intelligence Approaches

Zuleyha Yiner, Nurefsan Sertbas, Safak Durukan-Odabasi, Derya Yiltas-Kaplan
Copyright: © 2020 |Pages: 18
ISBN13: 9781799824664|ISBN10: 1799824667|EISBN13: 9781799824671
DOI: 10.4018/978-1-7998-2466-4.ch024
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MLA

Yiner, Zuleyha, et al. "Attack Detection in Cloud Networks Based on Artificial Intelligence Approaches." Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, IGI Global, 2020, pp. 377-394. https://doi.org/10.4018/978-1-7998-2466-4.ch024

APA

Yiner, Z., Sertbas, N., Durukan-Odabasi, S., & Yiltas-Kaplan, D. (2020). Attack Detection in Cloud Networks Based on Artificial Intelligence Approaches. In I. Management Association (Ed.), Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications (pp. 377-394). IGI Global. https://doi.org/10.4018/978-1-7998-2466-4.ch024

Chicago

Yiner, Zuleyha, et al. "Attack Detection in Cloud Networks Based on Artificial Intelligence Approaches." In Cyber Warfare and Terrorism: Concepts, Methodologies, Tools, and Applications, edited by Information Resources Management Association, 377-394. Hershey, PA: IGI Global, 2020. https://doi.org/10.4018/978-1-7998-2466-4.ch024

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Abstract

Cloud computing that aims to provide convenient, on-demand, network access to shared software and hardware resources has security as the greatest challenge. Data security is the main security concern followed by intrusion detection and prevention in cloud infrastructure. In this chapter, general information about cloud computing and its security issues are discussed. In order to prevent or avoid many attacks, a number of machine learning algorithms approaches are proposed. However, these approaches do not provide efficient results for identifying unknown types of attacks. Deep learning enables to learning features that are more complex, and thanks to the collection of big data as a training data, deep learning achieves more successful results. Many deep learning algorithms are proposed for attack detection. Deep networks architecture is divided into two categories, and descriptions for each architecture and its related attack detection studies are discussed in the following section of chapter.

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