Finger Knuckle Print Authentication Using AES and K-Means Algorithm

Finger Knuckle Print Authentication Using AES and K-Means Algorithm

Muthukumar Arunachalam1 and Kannan Subramanian2

1Department of Electronics and Communication Engineering, Kalasalingam University, India

2Department of Electrical and Electronics Engineering, Kalasalingam University, India

 

Abstract: In general, the identification and verification are done by passwords, PIN number, etc., which can be easily cracked by hackers. Biometrics is a powerful and unique tool based on the anatomical and behavioural characteristics of the human beings in order to prove their authentication. Security is the most important thing in the world. Password is used for security, but it does not provide the effective security. So biometrics can be used to provide the higher security than the password. Finger Knuckle Print (FKP) is a unique biometric anatomical feature for an individual person. Biometric systems are suffered to a variety of attacks. In order to avoid these attacks, the biometric combined cryptography is the major tool. Bio-crypto system is to provide the authentication as well as the confidentiality of the data. This paper presents biometric key, which is generated from key points of FKP using k-means algorithm and secret hash value also generated using Secure Hash Algorithm (SHA) function, which is encrypted with the FKP extracted key points by Symmetric  Advanced Encryption Standard (AES) algorithm. The key points extraction of FKP was derived using Scale Invariant Feature Transform (SIFT). Hence encrypted secret hash value secures biometric data and the secret value. The hash function protects the biometric data from malicious tampering, and it provides error checking functionality.

Keywords: Biometric cryptosystems, key point’s extraction, K-Means algorithm, SIFT algorithm, AES, SHA function.

                                                      Received August 30, 2012; accepted April 23, 2013                                                                                                                                                                      
Read 1991 times Last modified on Sunday, 16 August 2015 01:40
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