Enhancing Cloud Data Security with Confidential Computing and Secure Enclaves
Abstract
Protecting sensitive data in cloud environments is challenging due to exposure risks during processing. This paper introduces a confidential computing framework that leverages secure enclaves to isolate sensitive data and processing tasks from the cloud provider and other tenants. The framework uses hardware-based Trusted Execution Environments (TEEs) to encrypt data during computation, ensuring end-to-end confidentiality. Performance analysis demonstrates that the framework maintains low latency and high throughput while protecting sensitive data from insider and external threats. The study concludes that confidential computing enhances data security and privacy in multi-tenant cloud environments.
References
Krishna Madhav, J., Varun, B., Niharika, K., Srinivasa Rao, M., & Laxmana Murthy, K. (2023). Optimising Sales Forecasts in ERP Systems Using Machine Learning and Predictive Analytics. J Contemp Edu Theo Artific Intel: JCETAI-104.
Jha, K. M., Velaga, V., Routhu, K., Sadaram, G., Boppana, S. B., & Katnapally, N. (2025). Transforming Supply Chain Performance Based on Electronic Data Interchange (EDI) Integration: A Detailed Analysis. European Journal of Applied Science, Engineering and Technology, 3(2), 25-40.
Jha, K. M., Velaga, V., Routhu, K. K., Sadaram, G., & Boppana, S. B. (2025). Evaluating the Effectiveness of Machine Learning for Heart Disease Prediction in Healthcare Sector. J Cardiobiol, 9(1), 1.
KishanKumar Routhu, A. D. P. Risk Management in Enterprise Merger and Acquisition (M&A): A Review of Approaches and Best Practices.
Bodepudi, V. (2023). Understanding the Fundamentals of Digital Transformation in Financial Services: Drivers and Strategic Insights. Journal of Artificial Intelligence and Big Data, 3(1), 10-31586.
Jha, K. M., Bodepudi, V., Boppana, S. B., Katnapally, N., Maka, S. R., & Sakuru, M. Deep Learning-Enabled Big Data Analytics for Cybersecurity Threat Detection in ERP Ecosystems.
Boppana, S. B., Moore, C. S., Bodepudi, V., Jha, K. M., Maka, S. R., & Sadaram, G. AI And ML Applications In Big Data Analytics: Transforming ERP Security Models For Modern Enterprises.
Seelam, D. R., Kidiyur, M. D., Whig, P., Gupta, S. K., & Balantrapu, S. S. (2025). Integrating Artificial Intelligence in Blue-Green Infrastructure: Enhancing Sustainability and Resilience. In Integrating Blue-Green Infrastructure Into Urban Development (pp. 347-372). IGI Global Scientific Publishing.
Trehan, A. (2025). Bias in Green AI Addressing Disparities in Data and Algorithms. In Advancing Social Equity Through Accessible Green Innovation (pp. 63-76). IGI Global Scientific Publishing.
Trehan, A. (2025). The Road Ahead: AI and Data Science as Pillars for Sustainable Equity. In Advancing Social Equity Through Accessible Green Innovation (pp. 421-436). IGI Global Scientific Publishing.
Pradhan, C., & Trehan, A. (2025). Integration of Blockchain Technology in Secure Data Engineering Workflows.
Trehan, A., & Pradhan, C. AUTOMATED DATA LINEAGE TRACKING IN DATA ENGINEERING ECOSYSTEMS.
Katru, C. R., Gami, S. J., Shah, K. N., Trehan, A., & Saratchandran, D. V. (2024). Next-Gen AI Quality Checks: Redefining Data Integrity in Automated Workflows.
Juyal, P., Manukonda, P., Saratchandran, D., Trehan, A., Shah, K. N., & Rao, C. (2024). The Role of Artificial Intelligence in Enhancing Decision-Making in Enterprise Information Systems.
Pradhan, C., & Trehan, A. DATA ENGINEERING FOR SCALABLE MACHINE LEARNING DESIGNING ROBUST PIPELINES.
Shah, K., & Trehan, A. STREAMLINING SOFTWARE DEVELOPMENT: A COMPARATIVE STUDY OF AI-DRIVEN AUTOMATION TOOLS IN MODERN TECH.
Shah, K. N., Gami, S. J., & Trehan, A. An Intelligent Approach to Data Quality Management AI-Powered Quality Monitoring in Analytics.
Banerjee, S., & Parisa, S. K. (2023). AI-Powered Blockchain for Securing Retail Supply Chains in Multi-Cloud Environments. International Journal of Sustainable Development in computer Science Engineering, 9(9).
Banerjee, S., & Parisa, S. K. (2023). AI-Enhanced Intrusion Detection Systems for Retail Cloud Networks: A Comparative Analysis. Transactions on Recent Developments in Artificial Intelligence and Machine Learning, 15(15).
Parisa, S. K., Banerjee, S., & Whig, P. (2023). AI-Driven Zero Trust Security Models for Retail Cloud Infrastructure: A Next-Generation Approach. International Journal of Sustainable Devlopment in field of IT, 15(15).
Banerjee, S. (2023). Challenges and Solutions for Data Management in Cloud-Based Environments. International Journal of Advanced Research in Science, Communication and Technology, 370-378.
Parisa, S. K., & Banerjee, S. (2024). AI-Enabled Cloud Security Solutions: A Comparative Review of Traditional vs. Next-Generation Approaches. International Journal of Statistical Computation and Simulation, 16(1).
Banerjee, S., Whig, P., & Parisa, S. K. (2024). Leveraging AI for Personalization and Cybersecurity in Retail Chains: Balancing Customer Experience and Data Protection. Transactions on Recent Developments in Artificial Intelligence and Machine Learning, 16(16).
Banerjee, S., Whig, P., & Parisa, S. K. (2024). Cybersecurity in Multi-Cloud Environments for Retail: An AI-Based Threat Detection and Response Framework. Transaction on Recent Developments in Industrial IoT, 16(16).
Banerjee, S. (2024). Exploring Cryptographic Algorithms: Techniques, Applications, and Innovations. International Journal of Advanced Research in Science, Communication and Technology, 607-620.
