.png){kind=icon}
.png){kind=icon}
Return
Secure authentication using a multidimensional retinal biometric encryption method
.png){kind=icon}
OA
AI
DOI：10.1038/s41598-026-40962-0.png)
.png){kind=icon}
.png){kind=icon}
Share.png){kind=icon}
Save
Abstract
En 中文
Biometric encryption integrates physiological traits with cryptographic operations to improve authentication security. Retinal vasculature is particularly attractive due to its internal protection, permanence, and high inter-subject variability. we present a revised and rigorously justified multidimensional retinal encryption framework that generates three independent keys—RDDM (Retinal Diagonal Distance Metric), ROTD (Radial Origin-Terminus Distance), and DRID (Diagonal–Radial Intersection Distance)—from a single retinal vessel map. This framework is intended as a biometric-driven key generation and strengthening module to enhance user authentication, rather than a standalone standard encryption algorithm. It operates under a threat model focused on resisting brute-force key guessing in controlled biometric contexts, but not advanced attacks like quantum cryptanalysis or side-channel exploitation. Retinal images undergo preprocessing (CLAHE, vessel segmentation, skeletonization, endpoint detection) to extract stable endpoints. These endpoints produce distance measures that are normalized and combined into polyalphabetic key streams. We provide stepwise derivations of the encryption E(x) and decryption D(y) equations, explicitly justify mod 124 as the symbol table size used in implementation, and include a detailed cryptanalytic evaluation (entropy, NIST SP800-22 randomness tests, Hamming distance, collision analysis, noise sensitivity, and Full-Space Key Guessing (FSKG) calculations). Experimental results on three retinal samples (n_vessels = 27,41,105) show substantially increased FSKG times and near-maximal key entropy relative to single-key baselines. Limitations and sensitivity to image quality are discussed.
Keywords:
Retinal biometrics
Multidimensional keys
Cryptography
NIST randomness
FSKG
AI Summary
Key information extracted from the uploaded paper, including a brief overview, abstract, background, key highlights, visual analysis, and future outlook.
Journal
IF:
3.9
Papers:
27.8W
Citations:
83.5W