Fortifying cloud environments against data breaches: A novel AI-driven security framework

As cloud computing continues to dominate the modern technological landscape, organizations face growing challenges in preventing data breaches and sophisticated cyber threats. The increasing complexity and scale of cloud environments require advanced security mechanisms to address evolving threats. This paper introduces "SecureCloudAI," a cutting-edge AI-driven security framework designed to fortify sensitive data within cloud infrastructures. SecureCloudAI leverages a hybrid approach that combines machine learning models like Random Forest and deep learning techniques, including Long Short-Term Memory (LSTM) networks, to detect, classify, and respond to potential security breaches in real-time. The system offers robust malware detection, network traffic analysis, and web intrusion detection while maintaining scalability and efficiency across large cloud environments. Experimental results demonstrate SecureCloudAI's high accuracy, with malware detection at 94.78% and network traffic classification at 90.92%, ensuring the system can handle both complex and emerging threats. This AI-driven solution marks a significant advancement in cloud security, providing organizations with an adaptive and scalable tool to safeguard their data against the ever-growing cyber threat landscape.

Authors

Publication Details

Journal
World Journal of Advanced Research and Reviews
Published
2024-10-21
DOI
https://doi.org/10.30574/wjarr.2024.24.1.3194
Citations
16
Primary Topic
Network Security and Intrusion Detection
Type
article
Field-Weighted Citation Impact
5.58
Controls
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article

Fortifying cloud environments against data breaches: A novel AI-driven security framework

Akhila Reddy Yadulla, Vinay Kumar Kasula, Bhargavi Konda, Mounica Yenugula
16 citations
World Journal of Advanced Research and Reviews
Network Security and Intrusion Detection
5.58
article

Fortifying cloud environments against data breaches: A novel AI-driven security framework

Akhila Reddy Yadulla, Vinay Kumar Kasula, Bhargavi Konda, Mounica Yenugula
article en
16 citations

Abstract

As cloud computing continues to dominate the modern technological landscape, organizations face growing challenges in preventing data breaches and sophisticated cyber threats. The increasing complexity and scale of cloud environments require advanced security mechanisms to address evolving threats. This paper introduces "SecureCloudAI," a cutting-edge AI-driven security framework designed to fortify sensitive data within cloud infrastructures. SecureCloudAI leverages a hybrid approach that combines machine learning models like Random Forest and deep learning techniques, including Long Short-Term Memory (LSTM) networks, to detect, classify, and respond to potential security breaches in real-time. The system offers robust malware detection, network traffic analysis, and web intrusion detection while maintaining scalability and efficiency across large cloud environments. Experimental results demonstrate SecureCloudAI's high accuracy, with malware detection at 94.78% and network traffic classification at 90.92%, ensuring the system can handle both complex and emerging threats. This AI-driven solution marks a significant advancement in cloud security, providing organizations with an adaptive and scalable tool to safeguard their data against the ever-growing cyber threat landscape.

World Journal of Advanced Research and ReviewsVol. 24(1)
Openalex Percentile: Top 4%
Network Security and Intrusion Detection
5.58
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Fortifying cloud environments against data breaches: A novel AI-driven security framework — Akhila Reddy Yadulla, Vinay Kumar Kasula, et al. · World Journal of Advanced Research and Reviews (2024) | TGRS Research Map | TGRS