A Privacy-Preserving Cloud Data Security Framework with Advanced Encryption and Role-Based Access Control

Authors

  • Arvind Jagtap Department of Computer Engineering, Vidya Pratishthan's Kamalnayan Bajaj Institute of Engineering & Technology (VPKBIET), Baramati, Pune, Maharashtra, India.
  • Rahul Joshi Department of Computer Science and Engineering (CSE), Symbiosis Institute of Technology, Symbiosis International (Deemed University), Pune, Maharashtra, India.
  • Deepa Abin Department of Computer Science and Engineering (Data Science), Vishwakarma Institute of Technology, Pune, Maharashtra, India.
  • Jyoti Arvind Jagtap Department of General Science, Vidya Pratishthan's Kamalnayan Bajaj Institute of Engineering & Technology (VPKBIET), Baramati, Pune, Maharashtra, India.
  • Yogesh Manohar Gajmal Department of Computer Science and Engineering (Artificial Intelligence & Machine Learning), Finolex Academy of Management and Technology, Ratnagiri, Maharashtra, India.
  • Pravin Ramdas Patil SCTR's Pune Institute of Computer Technology (PICT), Savitribai Phule Pune University, Pune – 411043, Maharashtra, India.

DOI:

https://doi.org/10.70917/ijcisim-2026-2452

Keywords:

Cloud Data Security, Role-Based Access Control, Advanced Encryption Standard, Privacy-Preserving Architecture, Attribute-Based Encryption, Intrusion Detection System

Abstract

The growing use of cloud computing has greatly changed how data is stored and managed. However, this has led to new problems in data security and privacy. Existing cloud security frameworks offer little protection against complex cyber threats, especially in multi-tenant cloud systems, where data from different organizations can be stored in the same system. This problem, combined with insufficient advanced data protection structures and mechanisms for fine-grained access control, stresses the need for the development of new data protection systems. This paper examines several issues regarding the protection of data stored in the cloud, such as inadequate control of encryption keys, insufficient fine-grained access, the exposure of data to replay and man-in-the-middle attacks, performance problems due to high encryption efforts, and difficulties in the fulfillment of data protection regulations, such as the GDPR and HIPAA, in the cloud. This paper proposes a new protection system for the cloud, designed to secure data and maintain users’ privacy. The system combines a hybrid approach of the Advanced Encryption Standard, 256 (AES-256) and Rivest, Shamir, and Adelman (RSA-2048) encryption with a flexible Role-Based Access Control (RBAC). The system uses the intrusion detection system, Attribute-Based Encryption (ABE), and a hierarchical control of encryption keys. We have implemented the system and evaluated its performance on the cloud computing platform, Amazon Web Services (AWS), using test data of different sensitivity. In terms of data confidentiality, SPCDPA was found to be 98.7% accurate, with baseline systems reporting 94.3% more cases of data breaches. SPCDPA achieved a data encryption speed of 2.4 GB/s with a latency increase of only 12.3 ms. The system maintained a 1.2% false positive rate for intrusion detection and sustained performance for up to 10,000 users at a time. SPCDPA is highly scalable, secure, and comprehensive. The SPCDPA framework is a highly advanced data protection solution. The SPCDPA framework is a highly advanced data protection solution for cloud computing. The SPCDPA framework is also mathematically sound and provides a highly secure, practical, and highly deployable solution for protection cloud computing data. SPCDPA addresses the most current problems with security systems in cloud computing.

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Published

2026-06-28

How to Cite

Arvind Jagtap, Rahul Joshi, Deepa Abin, Jyoti Arvind Jagtap, Yogesh Manohar Gajmal, & Pravin Ramdas Patil. (2026). A Privacy-Preserving Cloud Data Security Framework with Advanced Encryption and Role-Based Access Control. International Journal of Computer Information Systems and Industrial Management Applications, 18(3s), 1207–1221. https://doi.org/10.70917/ijcisim-2026-2452

Issue

Section

Original Articles