Reliable Identity Management System Using Raspberry Pi

• Published in: 2020 2nd International Conference on Sustainable Technologies for Industry 4.0 (STI) pp. 1 - 6
• Main Authors: Rakib Hasan, Md, Chakraborty, Partha, Khatun, Mahmuda, Sarker, Aditi, Banerjee, Kawshik, Choudhury, Tanupriya, Abu Yousuf, Mohammad, Zahidur Rahman, Mohammad
• Format: Conference Proceeding
• Language: English
• Published: IEEE 19.12.2020
• Subjects: accurate technologies; AES encryption; Authentication; authorisation; authorized features; biometric authentication; biometric data matches; biometric features; biometrics (access control); costly embedded computer; cryptography; data privacy; feature extraction; final authentication process; fingerprint authentication; fingerprint enrollment; fingerprint identification; Fingerprint recognition; fingerprint recognition system; FLANN; image matching; Linux; Linux based computer; ORB; performing two factor authentication affixes more reliability; personal data; PyCrypto; python; python associated libraries; QR code generation; QR code reading; QR code validation; quality authentication model; raspberry Pi; Real-time systems; Reliability; reliable identity management system; storage management; stored one authorization; unique biological characteristics; zbar
• DOI: 10.1109/STI50764.2020.9350462

Biometric authentication, the process of verification using unique biological characteristics, is considered one of the most accurate technologies for authentication. It compares two or more biometric data to identify the differences among them properly. Based on the comparison between individual's biometric features and stored authorized features, it makes the decision of matched or mismatched. If the given sample of the biometric data matches with the stored one, authorization is confirmed. Nowadays, many real-time applications use biometric authentication to meet security purposes fully. However, it is difficult to implement fingerprint recognition system specially on Linux based computer. A well-known, less costly embedded computer called Raspberry Pi is used to build the entire system. Fingerprint enrollment, fingerprint recognition, photo capture, QR code generation as well as QR code reading were entirely done using python and python associated libraries. For storage management, we have used MySQL as it is convenient and open-source. This paper discusses about a quality authentication model which is highly capable and cost- effective. The authentication process consists of extracting the biometric features with ORB algorithm, matching those features using FLANN matcher, generating and validating QR code based on encrypted personal information accurately. Here, AES algorithm is used for encrypting personal data which is then converted and stored in form of QR code. Final authentication process involves both fingerprint and QR code validation. Performing two factor authentication affixes more reliability to the system.