The Role of AI and Machine Learning in Enhancing Cyber Security in Cloud Platforms

The growing reliance on cloud platforms has introduced a heightened need for robust cybersecurity measures. Traditional security methods, while effective, struggle to keep pace with evolving cyber threats. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative tools in enhancing cloud security, offering dynamic and automated approaches to threat detection, prevention, and response. This paper explores the critical role of AI and ML in addressing key cybersecurity challenges within cloud environments. It reviews various AI/ML techniques such as supervised learning, deep learning, and reinforcement learning, demonstrating their effectiveness in identifying vulnerabilities and responding to sophisticated cyberattacks. Through a discussion of real-world case studies, the paper highlights the advantages of integrating AI/ML models in cloud security architectures. Additionally, the paper identifies existing limitations, such as adversarial attacks on AI systems and ethical concerns related to data privacy. Finally, it outlines future directions for leveraging AI/ML in creating proactive, adaptive, and secure cloud environments.

Authors

Publication Details

Journal
Computer Fraud & Security
Published
2024-11-14
DOI
https://doi.org/10.52710/cfs.31
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
0.00
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article

The Role of AI and Machine Learning in Enhancing Cyber Security in Cloud Platforms

Nilesh P. Sable
1 links
Computer Fraud & Security
Network Security and Intrusion Detection
article

The Role of AI and Machine Learning in Enhancing Cyber Security in Cloud Platforms

Nilesh P. Sable
article en

Abstract

The growing reliance on cloud platforms has introduced a heightened need for robust cybersecurity measures. Traditional security methods, while effective, struggle to keep pace with evolving cyber threats. Artificial Intelligence (AI) and Machine Learning (ML) have emerged as transformative tools in enhancing cloud security, offering dynamic and automated approaches to threat detection, prevention, and response. This paper explores the critical role of AI and ML in addressing key cybersecurity challenges within cloud environments. It reviews various AI/ML techniques such as supervised learning, deep learning, and reinforcement learning, demonstrating their effectiveness in identifying vulnerabilities and responding to sophisticated cyberattacks. Through a discussion of real-world case studies, the paper highlights the advantages of integrating AI/ML models in cloud security architectures. Additionally, the paper identifies existing limitations, such as adversarial attacks on AI systems and ethical concerns related to data privacy. Finally, it outlines future directions for leveraging AI/ML in creating proactive, adaptive, and secure cloud environments.

Computer Fraud & Security
Openalex Percentile: Top 69%
Network Security and Intrusion Detection
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The Role of AI and Machine Learning in Enhancing Cyber Security in Cloud Platforms — Nilesh P. Sable · Computer Fraud & Security (2024) | TGRS Research Map | TGRS