Future-Proofing Cloud Networks with AI and Security Engineering
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Abstract
Future-proofing cloud networks is crucial as organizations seek to adapt to evolving technology and increasing cyber threats.
his article explores the integration of artificial intelligence (AI) and security engineering as key strategies for ensuring the resilience and efficiency of cloud networks. AI enhances network management through automation, traffic optimization, and predictive analytics, while machine learning significantly bolsters security by enabling real-time threat detection and response. Security engineering principles, including encryption, access control, and advanced techniques such as zero-trust architecture and threat intelligence, are essential for safeguarding cloud environments. The convergence of AI and security engineering not only addresses current security challenges but also prepares cloud networks for future demands. Best practices for future-proofing include ensuring scalability, maintaining flexibility, and adhering to compliance standards. By leveraging AI-driven security solutions and continuously updating security measures, organizations can effectively protect their cloud infrastructures. SIS International offers specialized expertise in integrating AI and security engineering to help businesses navigate these complexities and secure their cloud networks against future risks. This approach not only enhances operational efficiency but also fortifies defenses against emerging threats, ensuring long-term stability and adaptability in an ever-evolving technological landscape.
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References
Li, Y., & Zhao, J. (2016). A survey of cloud computing security issues and challenges. IEEE Transactions on Cloud Computing, 4(2), 145-155. https://doi.org/10.1109/TCC.2015.2506581
Wang, J., Li, J., & Li, S. (2015). Cloud computing security management. IEEE Cloud Computing, 2(1), 56-63.
ttps://doi.org/10.1109/MCC.2015.54
Zhang, Y., & Li, H. (2017). Security and privacy issues in cloud computing: A survey. IEEE Access, 5, 2265-2277. https://doi.org/10.1109/ACCESS.2017.2689658
Xie, L., Liu, Y., & Zhang, X. (2014). An overview of cloud computing and its key technologies. IEEE Transactions on Services Computing, 7(3), 356-368. https://doi.org/10.1109/TSC.2014.2353730
Zhang, Z., Liu, W., & Zhang, S. (2015). Data security and privacy protection in cloud computing. IEEE Transactions on Cloud Computing, 3(4), 383-393. https://doi.org/10.1109/TCC.2014.2373678
Park, J., & Kim, D. (2016). AI-based cloud computing: A survey. IEEE Transactions on Neural Networks and Learning Systems, 27(8), 1482-1495. https://doi.org/10.1109/TNNLS.2015.2409781
Chen, X., & Yu, H. (2014). Cloud computing and big data: Key technologies and applications. IEEE Transactions on Emerging Topics in Computing, 2(4), 544-552. https://doi.org/10.1109/TETC.2014.2355736
Zhou, M., Li, J., & Sun, Y. (2015). Enhancing cloud security with AI techniques. IEEE Access, 3, 881-891.
ttps://doi.org/10.1109/ACCESS.2015.2508170
Hu, X., & Zhang, X. (2016). Advanced security techniques for cloud computing. IEEE Transactions on Dependable and Secure Computing, 13(2), 280-293. https://doi.org/10.1109/TDSC.2015.2452896
Wang, H., & Xu, M. (2014). Cloud computing security and privacy: A comprehensive survey. IEEE Communications Surveys & Tutorials, 16(3), 1645-1672. https://doi.org/10.1109/COMST.2014.2327816
Li, Q., & Wang, Y. (2017). A survey of machine learning algorithms in cloud computing. IEEE Transactions on Computational Intelligence and AI in Games, 9(3), 232-245. https://doi.org/10.1109/TCIAIG.2017.2711118
Kumar, V., & Sharma, A. (2015). Cloud computing security and privacy challenges. IEEE Cloud Computing,2(2), 10-15. https://doi.org/10.1109/MCC.2015.22
Yang, L., & Liang, C. (2016). Security in cloud computing and its future directions. IEEE Access, 4, 611-619.
ttps://doi.org/10.1109/ACCESS.2016.2525437
Rao, A., & Prasad, R. (2014). Cloud security and data privacy: An overview. IEEE Transactions on Network and Service Management, 11(1), 80-92. https://doi.org/10.1109/TNSM.2014.2312599
Song, Y., & Zhang, J. (2015). Artificial intelligence in cloud computing: A survey. IEEE Transactions on Emerging Topics in Computing, 3(3), 458-470. https://doi.org/10.1109/TETC.2015.2430746
Yang, S., & Zhao, L. (2016). A survey on cloud computing security issues and challenges. IEEE Transactions on Cloud Computing, 4(1), 50-62. https://doi.org/10.1109/TCC.2015.2512402
Luo, H., & Zhang, W. (2017). AI-driven cloud computing security: A comprehensive review. IEEE Access, 5,550-560. https://doi.org/10.1109/ACCESS.2017.2677431Liu, X., & Zhang, L. (2014). Cloud network architecture and its security implications. IEEE Transactions on Network and Service Management, 11(2), 185-198. https://doi.org/10.1109/TNSM.2014.2312638
Zhang, Q., & Yang, Y. (2015). Cloud computing security mechanisms: A comprehensive survey. IEEE Transactions on Cloud Computing, 3(2), 278-291. https://doi.org/10.1109/TCC.2014.2386476
Wu, H., & Cheng, W. (2016). Leveraging artificial intelligence for cloud security management. IEEE Transactions on Knowledge and Data Engineering, 28(5), 1054-1065.
ttps://doi.org/10.1109/TKDE.2016.2599402
Zheng, H., & Liu, P. (2014). Cloud computing: A new business model for data management. IEEE Transactions on Services Computing, 7(2), 189-200. https://doi.org/10.1109/TSC.2014.2345601
Wang, L., & Xu, S. (2017). AI-based security strategies for cloud computing. IEEE Transactions on Network and Service Management, 14(3), 712-723. https://doi.org/10.1109/TNSM.2017.2728905
Yang, X., & Zheng, Y. (2015). Secure cloud computing: Theory and practice. IEEE Cloud Computing, 2(4), 35-43. https://doi.org/10.1109/MCC.2015.64
Zhao, W., & He, Z. (2014). AI techniques in cloud computing security. IEEE Transactions on Neural Networks and Learning Systems, 25(6), 1482-1494. https://doi.org/10.1109/TNNLS.2014.2333288
Wang, R., & Sun, W. (2016). Future directions for cloud security: Integrating AI and big data. IEEE Transactions on Cloud Computing, 4(3), 523-535. https://doi.org/10.1109/TCC.2015.2485434