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Volume 13 | Issue 5 | Year 2026 | Article Id. IJECE-V13I5P105 | DOI : https://doi.org/10.14445/23488549/IJECE-V13I5P105

Decentralized Predictive Intelligence for Fabricated Entity Detection in Blockchain-Integrated Identity Systems

Naveen Gajji, Ramesh babu Akarapu

Received Revised Accepted Published
06 Feb 2026 07 Mar 2026 06 Apr 2026 27 May 2026

Citation :

Naveen Gajji, Ramesh babu Akarapu, "Decentralized Predictive Intelligence for Fabricated Entity Detection in Blockchain-Integrated Identity Systems," International Journal of Electronics and Communication Engineering, vol. 13, no. 5, pp. 41-57, 2026. Crossref, https://doi.org/10.14445/23488549/IJECE-V13I5P105

Abstract

The study postulates a novel approach that leverages blockchain technology for use in predictive analytics, which will serve as a mechanism for predicting the fabrication of an entity in the course of digitally verifying identity. The introduction of blockchain technology has offered a platform that is transparent, secure, and immutable, which has led to the extraction of sophisticated predictive models that eliminate and detect the threats presented by synthetic identity fraud. The approach that authors have suggested has been proven to be highly precise with regard to the estimation of the probability of deceptive behavior by scanning the route and errors contained in the transactional and behavioral data stored on the blockchain. This article has presented a well-founded system, based on a combination of historical data analysis and machine learning algorithms, and which uses the features of blockchain technology to produce a strong system that validates digital identities. The system has not only produced a strengthened security and integrity of digital identities, but also gives a proactive approach to preventing fraud through predictive analysis, which found early indications of entity fabrication, permitting early intervention and prevention of the fraud occurring. Additionally, making use of this predictive analysis system based on blockchain technology, the system has shown a significantly increased efficiency and reliability in reference to the procedure employed to confirm the digital identities. The number of mistakes in the form of false positives has been significantly reduced, and thus, the trust between the provider and the user services has been enhanced. The predictive analytics model offered integrity and transparency by decentralization of blockchain for enhanced user confidence in internet transactions. The research has offered a distinct and effective means of predicting and averting the incidence of synthetic identity fraud on the internet. The predictive analytics platform based on the blockchain has addressed the current problem of online identity verification and developed a new tier of security associated with online interaction. The offered approach can transform the sphere of digital identity verification and improve its level of security, efficiency, and reliability.

Keywords

Blockchain; Digital Identity Verification; Gradient Boosting Machine; Mutual Information (MI); Predictive Analytics.

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