Role-Based access Control (RBAC) and Attribute-Based Access Control (ABAC)

Author:

Khan Javed Akhtar1

Affiliation:

1. Gyan Ganga College of Technology, India

Abstract

This chapter explores the profound impact of artificial intelligence (AI) and machine learning (ML) on the realm of cloud security. As organizations increasingly migrate their operations and data to cloud environments, ensuring robust security measures becomes paramount. The integration of AI and ML technologies introduces novel ways to enhance threat detection, prevention, and response in the cloud. This chapter delves into various aspects of this synergy, discussing the benefits, challenges, and future prospects of utilizing AI and ML for safeguarding cloud infrastructures. This chapter also presents the benefits, challenges, and future directions. This abstract underscores the transformative potential of AI and ML in fortifying cloud infrastructures and safeguarding sensitive information in the digital age.

Publisher

IGI Global

Reference4 articles.

1. Achar, S. (2022). Adopting Artificial Intelligence and Deep learning techniques in cloud computing. Research Gate. https://www.researchgate.net/profile/Sandesh-Achar/publication/366205412_Adopting_Artificial_Intelligence_and_Deep_Learning_Techniques_in_Cloud_Computing_for_Operational_Efficiency/links/6397a7df11e9f00cda3de394/Adopting-Artificial-Intelligence-and-Deep-Learning-Techniques-in-Cloud-Computing-for-Operational-Efficiency.pdf

2. Ali, A. (2017). Unsupervised feature learning and automatic modulation classification using deep learning. Physical Communication, 25(1).

3. Bresniker, K. (2019). Grand Challenge. Computer, 52(12). https://ieeexplore.ieee.org/abstract/document/8909930

4. Harvard Press. (n.d.). Privacy Preserving Machine Learning. Harvard Press.

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