Secure Multi-Tenancy in Cloud-Based SaaS Applications Using Attribute-Based Access Control (ABAC)
Abstract
Multi-tenant SaaS (Software as a Service) applications face challenges in ensuring data isolation and secure access. This paper proposes an attribute-based access control (ABAC) framework for secure multi-tenancy in cloud-based SaaS applications. The framework assigns access permissions based on user attributes, organizational policies, and contextual factors. Role hierarchy and dynamic attribute evaluation ensure that access control policies are enforced in real time. Performance evaluations demonstrate that the ABAC framework enhances security and scalability without compromising user experience. The study concludes that ABAC offers a flexible and robust approach to securing multi-tenant SaaS applications.
References
Chinta, P. C. R., Katnapally, N., Ja, K., Bodepudi, V., Babu, S., & Boppana, M. S. (2022). Exploring the role of neural networks in big data-driven ERP systems for proactive cybersecurity management. Kurdish Studies.
Routhu, K., Bodepudi, V., Jha, K. M., & Chinta, P. C. R. (2020). A Deep Learning Architectures for Enhancing Cyber Security Protocols in Big Data Integrated ERP Systems. Available at SSRN 5102662.
Moore, C. (2023). AI-powered big data and ERP systems for autonomous detection of cybersecurity vulnerabilities. Nanotechnology Perceptions, 19, 46-64.
Bodepudi, V., & Chinta, P. C. R. (2024). Enhancing Financial Predictions Based on Bitcoin Prices using Big Data and Deep Learning Approach. Available at SSRN 5112132.
Chinta, P. C. R. (2023). The Art of Business Analysis in Information Management Projects: Best Practices and Insights. DOI, 10.
Chinta, P. C. R., & Katnapally, N. (2021). Neural Network-Based Risk Assessment for Cybersecurity in Big Data-Oriented ERP Infrastructures. Neural Network-Based Risk Assessment for Cybersecurity in Big Data-Oriented ERP Infrastructures.
Katnapally, N., Chinta, P. C. R., Routhu, K. K., Velaga, V., Bodepudi, V., & Karaka, L. M. (2021). Leveraging Big Data Analytics and Machine Learning Techniques for Sentiment Analysis of Amazon Product Reviews in Business Insights. American Journal of Computing and Engineering, 4(2), 35-51.
Chinta, P. C. R., Moore, C. S., Karaka, L. M., Sakuru, M., Bodepudi, V., & Maka, S. R. (2025). Building an Intelligent Phishing Email Detection System Using Machine Learning and Feature Engineering. European Journal of Applied Science, Engineering and Technology, 3(2), 41-54.
Moore, C. (2024). Enhancing Network Security With Artificial Intelligence Based Traffic Anomaly Detection In Big Data Systems. Available at SSRN 5103209.
Chinta, P. C. R., Moore, C. S., Karaka, L. M., Sakuru, M., & Bodepudi, V. (2025). Predictive Analytics for Disease Diagnosis: A Study on Healthcare Data with Machine Learning Algorithms and Big Data. J Cancer Sci, 10(1), 1.
Chinta, P. C. R., Jha, K. M., Velaga, V., Moore, C., Routhu, K., & SADARAM, G. (2024). Harnessing Big Data and AI-Driven ERP Systems to Enhance Cybersecurity Resilience in Real-Time Threat Environments. Available at SSRN 5151788.
BOPPINITI, S. T. (2018). Human-Centric Design for IoT-Enabled Urban Health Solutions: Beyond Data Collection. International Transactions in Artificial Intelligence, 2(2).
BOPPINITI, S. T. (2018). Unraveling the Complexities of Healthcare Data Governance: Strategies, Challenges, and Future Directions. Transactions on Latest Trends in IoT, 1(1), 73-89.
BOPPINITI, S. T. (2017). Privacy-Preserving Techniques for IoT-Enabled Urban Health Monitoring: A Comparative Analysis. International Transactions in Artificial Intelligence, 1(1).
BOPPINITI, S. T. (2016). Core Standards and Applications of Big Data Analytics. International Journal of Sustainable Development in computer Science Engineering, 2(2).
BOPPINITI, S. T. (2015). Revolutionizing Industries with Machine Learning: A Global Insight. International Journal of Sustainable Development in computer Science Engineering, 1(1).
BOPPINITI, S. T. (2014). Emerging Paradigms in Robotics: Fundamentals and Future Applications. Transactions on Latest Trends in Health Sector, 6(6).
Boppiniti, S. T. (2023). AI-Powered Disease Outbreak Prediction Using Environmental and Social Data. International Transactions in Machine Learning, 5(5).
Boppiniti, S. T. (2021). AI-Based Cybersecurity for Threat Detection in Real-Time Networks. International Journal of Machine Learning for Sustainable Development, 3(2).
BOPPINITI, S. T. (2019). Revolutionizing Healthcare Data Management: A Novel Master Data Architecture for the Digital Era. Transactions on Latest Trends in IoT, 2(2).
Boppiniti, S. T. (2017). Revolutionizing Diagnostics: The Role of AI in Early Disease Detection. International Numeric Journal of Machine Learning and Robots, 1(1).
Boppiniti, S. T. (2018). AI-Powered Predictive Analytics for Personalized Healthcare. International Numeric Journal of Machine Learning and Robots, 2(2).
Boppiniti, S. T. (2018). AI-Driven Drug Discovery: Accelerating the Path to New Therapeutics. International Machine learning journal and Computer Engineering, 1(1).
Boppiniti, S. T. (2019). Natural Language Processing in Healthcare: Enhancing Clinical Decision Support Systems. International Numeric Journal of Machine Learning and Robots, 3(3).
Boppiniti, S. T. (2020). AI in Mental Health: Opportunities and Challenges in Psychological Care. International Numeric Journal of Machine Learning and Robots, 4(4).
Boppiniti, S. T. (2021). AI and Robotics in Surgery: Enhancing Precision and Outcomes. International Numeric Journal of Machine Learning and Robots, 5(5).
Boppiniti, S. T. (2022). AI for Dynamic Traffic Flow Optimization in Smart Cities. International Journal of Sustainable Development in Computing Science, 4(4).
Boppiniti, S. T. (2022). Ethical Dimensions of AI in Healthcare: Balancing Innovation and Responsibility. International Machine learning journal and Computer Engineering, 5(5).
Boppiniti, S. T. (2023). Edge AI for Real-Time Object Detection in Autonomous Vehicles. Transactions on Recent Developments in Health Sectors, 6(6).
