Enabling Secure Data Sharing in Big Data Ecosystems Through Advanced Access Control Models Article Swipe
YOU?
·
· 2024
· Open Access
·
· DOI: https://doi.org/10.36948/ijfmr.2024.v06i03.51730
· OA: W4412663347
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.
