IBMESR: Towards next-generation big data security with integrated blockchain model for efficient, scalable, and robust operations

Abstract

Sophisticated security mechanisms for the integrity, trust, and availability of data in such big data environments have been developed, especially in multi-cloud scenarios. Most of these traditional solutions suffer from latency, energy inefficiency, and unauthorized access. Traditional models for security are mostly based on static encryption and proof mechanisms, which are inadequate, result in high data processing delays, high energy consumption, and low throughput. Often, such models are quite unsuccessful in detecting unauthorized access attempts, thereby increasing security risks. In this paper, we introduce a new security framework that refers to an IBMESR—an outline of an integrated blockchain model for efficient, scalable, and robust operations in big data environments. In the proposed architecture, state-of-the-art technologies are incorporated that support proof of spatial and temporal trust-based blockchain for secured data storage, grey wolf optimization for efficient blockchain sharding, fully homomorphic encryption for securing data across distributed nodes, physical unclonable functions for inter-node resilient communications, and fuzzy rule-based access control to improve security at large. Empirical evaluations have proven that IBMESR can reduce the inefficiencies and vulnerabilities of existing models by an average of 8.3 % in terms of data processing delays, 4.5 % in energy consumption, and 2.9 % in communication throughput, with improvements in security of 8.5 % in terms of attack detection accuracy and access speed of 3.5 %. This framework is an innovation in big data security that is explicitly designed to provide a comprehensive solution to problems that exist with current approaches and, therefore, contributes to more secure, efficient, and robust big data ecosystems.