Block chain Enabled Bigdata solutions for secure &Transparent Data systems

Sunil Kr., Pandey and G., Vannurswamy and Harjinder, Kaur and GAYATHRI DEVI, S and Rakesh, Dani and Ranjeeta, Yadav (2026) Block chain Enabled Bigdata solutions for secure &Transparent Data systems. In: International Conference on Sustainable Computing & Intelligent Systems. (In Press)

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Abstract

Big data has exponentially grown and highly posed challenges for the safety, integrity, and transparency of data. Traditional centralized systems are vulnerable to breaches and tampering, prompting the need for innovation. Blockchain technology offers a revolutionary approach in that it is decentralized, immutable, and transparent by nature. Thus, this paper explores blockchain-enabled solutions for big data systems based on their ability to enhance security and transparency. We explore methodologies recently researched, such as hashed timelock contracts (HTLCs), decentralized storage frameworks, and simulation-based validation techniques. Such methods proved robust data integrity and transparency under varied network conditions. Our results prove that the integration of blockchain significantly increases data integrity with auditable and tamper-proofing records The decentralized nature of blockchain prevents the issue of single points of failure, so basically, it provides security resilience. On top of this, though, there are two other big challenges which might make it difficult-scopal reachability and energy efficiency. The technical advancement can restrict wide acceptance despite it. This research delineates a unified framework improving capabilities for large data systems using blockchain, overcoming such limits and unlocking its potential. This research sheds light on the major benefits along with areas of improvement and contributes to the establishment of safe and transparent data ecosystems enabled by blockchain technology.

Item Type: Conference or Workshop Item (Paper)
Subjects: Computer Science Engineering > Big Data
Domains: Computer Science Engineering
Depositing User: Mr IR Admin
Date Deposited: 18 May 2026 06:49
Last Modified: 18 May 2026 15:57
URI: https://ir.vistas.ac.in/id/eprint/20047

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