Generating an Iris-based Seed for Key-pairs in a Blockchain Platform

Authentication is a critical concern in cybersecurity, and the challenge of combining security with ease of use remains a pressing issue. Biometric authentication methods, particularly iris recognition, leverage unique physical characteristics to confirm identity, presenting an effective solution to enhance security over traditional password systems. However, the management of sensitive biometric data requires privacy measures to protect user information from potential misuse. This work proposes a novel Blockchain-based system that utilizes biometric data, specifically iris scans, as a seed for generating cryptographic key-pairs. By employing feature extraction and hashing techniques, the system ensures that sensitive biometric information is neither stored centrally nor accessible in its original form, thereby preserving user anonymity and privacy. The architecture is designed to distribute fragmented biometric data across multiple nodes in the Blockchain, enhancing scalability and security. The system’s functionality is validated through extensive testing scenarios that demonstrate its reliability and robustness in various operational conditions. This research highlights the potential of combining Blockchain technology with biometric authentication to create secure and privacy-preserving identity management solutions, paving the way for applications in sectors such as finance, healthcare, and secure voting systems.

Authors

Institutions

Publication Details

Journal
Journal of Communications Software and Systems
Published
2025-01-01
DOI
https://doi.org/10.24138/jcomss-2024-0100
Citations
1
Primary Topic
User Authentication and Security Systems
Type
article
Field-Weighted Citation Impact
3.25
Controls
|||
ALL TIME
JAN
FEB
MAR
APR
MAY
JUN
JUL
AUG
SEP
OCT
article

Generating an Iris-based Seed for Key-pairs in a Blockchain Platform

G. Coppola, Marina Mongiello, Federico Carrozzino, Marco Fiore et al.
1 citations
Journal of Communications Software and Systems
User Authentication and Security Systems
3.25
article

Generating an Iris-based Seed for Key-pairs in a Blockchain Platform

G. Coppola, Marina Mongiello, Federico Carrozzino, Marco Fiore, Gianni Guariglia
article en
1 citations

Abstract

Authentication is a critical concern in cybersecurity, and the challenge of combining security with ease of use remains a pressing issue. Biometric authentication methods, particularly iris recognition, leverage unique physical characteristics to confirm identity, presenting an effective solution to enhance security over traditional password systems. However, the management of sensitive biometric data requires privacy measures to protect user information from potential misuse. This work proposes a novel Blockchain-based system that utilizes biometric data, specifically iris scans, as a seed for generating cryptographic key-pairs. By employing feature extraction and hashing techniques, the system ensures that sensitive biometric information is neither stored centrally nor accessible in its original form, thereby preserving user anonymity and privacy. The architecture is designed to distribute fragmented biometric data across multiple nodes in the Blockchain, enhancing scalability and security. The system’s functionality is validated through extensive testing scenarios that demonstrate its reliability and robustness in various operational conditions. This research highlights the potential of combining Blockchain technology with biometric authentication to create secure and privacy-preserving identity management solutions, paving the way for applications in sectors such as finance, healthcare, and secure voting systems.

Journal of Communications Software and SystemsVol. 21(2)
Polytechnic University of Bari (IT)
Openalex Percentile: Top 9%
User Authentication and Security Systems
3.25
AI Navigator

Ask Laika to Summarize, Analyze, and Connect papers live on the map.

Summarize Papers & Methodologies

Extract key findings, datasets, and comparative methods across publications.

Benchmark Rankings & Visual Analytics

Rank top research institutions, authors, funders, topics, and journals by Field-Weighted Citation Impact (FWCI) and paper volume with instant charts.

Connect Distant Disciplines

Bridge topological clusters on the map to find hidden collaborative intersections.