DYNAMIC THREAT DETECTION IN CLOUD ENVIRONMENTS USING AI-DRIVEN ZERO TRUST ARCHITECTURE
Keywords:
Cloud Security, Zero Trust Architecture, AI-Driven Security, Threat Detection, Dynamic Security Policies, Machine Learning in CybersecurityAbstract
With the growing dependence on cloud services across industries, security challenges have evolved, making traditional perimeter-based defense models inadequate. This paper presents an AI-driven Zero Trust Architecture (ZTA) for cloud environments, emphasizing real-time dynamic threat detection. By leveraging machine learning (ML) and deep learning (DL) algorithms for continuous monitoring and risk assessment, our proposed system can effectively adapt to emerging threats while minimizing false positives. Experimental results show a significant improvement in threat detection accuracy, response time, and system performance compared to conventional cloud security approaches.
References
Shrobe, H., Smith, C., & Wysopal, C. (2023). Zero Trust Architecture: Design Principles for Enhanced Cybersecurity. IEEE Security & Privacy, 21(1), 25-33. https://doi.org/10.1109/MSP.2023.3018492
Huang, C., Wang, Y., & Zhou, X. (2023). AI-Driven Cloud Security: From Theory to Practice. Journal of Cloud Computing, 12(4), 455-469. https://doi.org/10.1186/s13677-023-00231-9
Khouzani, M., & Kumar, A. (2022). Deep Learning for Intrusion Detection in Cloud Environments. IEEE Transactions on Cloud Computing, 10(2), 356-368. https://doi.org/10.1109/TCC.2021.3106749
Wu, Z., Zhang, Q., & Tang, C. (2023). Dynamic Threat Detection Using Machine Learning in Zero Trust Frameworks. ACM Computing Surveys, 55(7), 130-145. https://doi.org/10.1145/3514230
Sharma, P., Gupta, R., & Mukherjee, P. (2022). Zero Trust Security in Cloud: Challenges and Opportunities. IEEE Transactions on Network and Service Management, 19(1), 67-82. https://doi.org/10.1109/TNSM.2022.3132156
Qin, Y., Liu, H., & Song, Y. (2022). AI-Based Real-Time Anomaly Detection in Cloud Systems. Journal of Network and Computer Applications, 207(1), 103520. https://doi.org/10.1016/j.jnca.2022.103520
Kim, J., Park, S., & Oh, H. (2023). Exploring AI Capabilities for Zero Trust Implementation in Cloud Environments. Journal of Cybersecurity and Privacy, 5(2), 182-197. https://doi.org/10.3390/jcp5020014
Azmoodeh, A., & Dehghantanha, A. (2022). Leveraging Artificial Intelligence for Cloud Threat Intelligence and Response. Future Generation Computer Systems, 135(1), 423-433. https://doi.org/10.1016/j.future.2022.04.030
Ahmed, S., Yao, Z., & Tian, Z. (2023). Machine Learning Applications in Cybersecurity: A Survey on Cloud-Based Systems. ACM Computing Surveys, 55(3), 1-28. https://doi.org/10.1145/3527161
Fan, X., Sun, L., & Li, W. (2023). Mitigating Cloud Security Threats through AI-Enhanced Zero Trust Models. Proceedings of the 2023 IEEE International Conference on Cloud Computing, 156-165. https://doi.org/10.1109/CLOUD.2023.00123
Downloads
Published
How to Cite
Issue
Section
License
Copyright (c) 2023 COMPUSOFT: An International Journal of Advanced Computer Technology
This work is licensed under a Creative Commons Attribution 4.0 International License.
©2023. COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY by COMPUSOFT PUBLICATION is licensed under a Creative Commons Attribution 4.0 International License. Based on a work at COMPUSOFT: AN INTERNATIONAL OF ADVANCED COMPUTER TECHNOLOGY. Permissions beyond the scope of this license may be available at Creative Commons Attribution 4.0 International Public License.
