Enabling Secure Data Sharing in Big Data Ecosystems Through Advanced Access Control Models

Author(s)	Priyam Vaghasia, Dhruvitkumar Patel
Country	United States
Abstract	The rapid expansion of big data ecosystems has necessitated robust mechanisms to ensure secure data sharing while maintaining scalability and compliance. Traditional access control models, such as Role-Based Access Control (RBAC), struggle to address the dynamic, distributed nature of modern systems. This paper investigates advanced frameworks, including Dynamic Attribute-Based Access Control (ABAC), blockchain-enabled decentralization, and machine learning-driven adaptive policies, to bridge these gaps. Cryptographic techniques like homomorphic encryption and differential privacy are evaluated for privacy preservation, while interoperability standards such as XACML and federated identity management are analyzed for cross-platform compatibility. Performance benchmarks reveal hybrid ABAC-blockchain architectures reduce policy evaluation latency by 40% compared to RBAC. The study concludes with recommendations for integrating Zero-Trust Architecture (ZTA) and quantum-resistant algorithms into future systems.
Keywords	Access Control, Big Data Security, ABAC, Blockchain, Homomorphic Encryption, Zero-Trust Architecture.
Field	Engineering
Published In	Volume 6, Issue 3, May-June 2024
Published On	2024-06-07
DOI	https://doi.org/10.36948/ijfmr.2024.v06i03.51730

About IJFMR Fees & Payment Current Issue Publication Archive	Submit Research Paper Track Submission Status Publication Guidelines Publication Ethics Peer Review & Plagiarism	Join as a Reviewer Editors & Reviewers Reviewer Referral Program Get Reviewer Membership Certi.	Website/Journal Policies Usage Policy Content Policies Privacy Policy

Contact Us		+91-9687-828-838	editor@ijfmr.com

International Journal For Multidisciplinary Research