Impact Factor
Call For Paper
Volume 12 Issue 07
July 2026
Author(s)
Abstract
Airport Authority Systems Demand The Highest Levels Of Security For Controlling Access To Restricted Zones, Yet Traditional Authentication Mechanisms Based On Identity Cards, PINs, And Passwords Remain Inherently Susceptible To Theft, Forgery, Duplication, And Social Engineering Attacks. Biometric Authentication Offers A More Reliable Alternative; However, Conventional Face Recognition Systems Face Critical Challenges Including Spoofing Vulnerabilities, Inadequate Privacy Preservation For Stored Biometric Templates, And Limited Accuracy In Live-face Detection. This Paper Proposes A Privacy-Enhanced Crypto-Biometric Authentication Framework (PECBAF) Specifically Tailored For Airport Authority Access Control, Extending The Cancellable Template Protection Scheme Of Imran Et Al. [1] To The Facial Biometric Domain. The Proposed Framework Integrates The Grassmann Manifold Algorithm For Live Facial Feature Extraction, Deriving Approximately 1024 Discriminative Features From 76 Key Facial Landmark Points. The Extracted Facial Feature Subspace Representation Is Subjected To A Möbius Conformal Transformation Parameterized By A User-specific Keyset (p, Q), Generating A Non-invertible Cancellable Biometric Template That Cannot Be Reconstructed From Stored Data Even Under Database Compromise. The Cancellable Template Is Subsequently Secured Using A Dual-layer Hybrid Encryption Scheme Combining 256-bit AES With RSA Public-key Cryptography, Safeguarding Template Integrity Against Spoofing, Brute-force, And Cross-database Attacks. An Access Control Module Enforces Role-based Entry Decisions With Real-time Audit Logging. The Proposed System Is Evaluated In Terms Of Revocability, Unlinkability, Non-invertibility, And Authentication Accuracy. Results Demonstrate High Genuine Acceptance Rates With Low False Acceptance Rates, Confirming The System's Suitability For High-security Airport Environments. The Framework Provides A Robust, Privacy-preserving, And Computationally Efficient Alternative To Conventional Airport Biometric Systems.
Keywords
Paper ID
IJSARTV12I4105062
Publication Date
April 18, 2026
Research Area
Computer Science And Engineering