A digest-based method for efficiency improvement of security in biometrical cryptography authentication

All biometrie cryptographic algorithms need a secret key or a random number as an ID or biometrie information to identify an individual that aims to enter the system. The biometrie information is unique and trustable for making an authentication system. Most of current schemes utilize encryption/decryption methods including RSA to make secure data from primary biometric information. Generally, encrypting and decrypting algorithms have slow and time-consuming operations. Comparing information of an individual aims to enter the system with that of the authorized clients in database is a complex issue that has motivated researchers to examine the possibility of chance and likely combinations. In this paper, we propose a new concept called “digest” to provide an authorization system that should work properly with any set of biometric traits. The digest value together with the systems parameters are used by the matching module for the authentication. Through the digest, nobody can capture any information of primary biometric traits. The properties mentioned above lead to increases of the accuracy, accessibility and easiness level of a biometric system.

[1]  Christoph Busch,et al.  Towards standardizing trusted evidence of identity , 2013, Digital Identity Management.

[2]  Ann Cavoukian,et al.  Biometric Encryption , 2011, Encyclopedia of Cryptography and Security.

[3]  Mohammad Shahram Moin,et al.  A New User Dependent Iris Recognition System Based on an Area Preserving Pointwise Level Set Segmentation Approach , 2009, EURASIP J. Adv. Signal Process..

[4]  K. Srinathan,et al.  Blind Authentication: A Secure Crypto-Biometric Verification Protocol , 2010, IEEE Transactions on Information Forensics and Security.

[5]  Julien Bringer,et al.  Error-Tolerant Searchable Encryption , 2009, 2009 IEEE International Conference on Communications.

[6]  Julien Bringer,et al.  An Authentication Protocol with Encrypted Biometric Data , 2008, AFRICACRYPT.

[7]  Madhu Sudan,et al.  A Fuzzy Vault Scheme , 2006, Des. Codes Cryptogr..

[8]  Ghassan O. Karame,et al.  Low-Cost Client Puzzles Based on Modular Exponentiation , 2010, ESORICS.

[9]  Andreas Uhl,et al.  A survey on biometric cryptosystems and cancelable biometrics , 2011, EURASIP J. Inf. Secur..

[10]  Julien Bringer,et al.  Identification with encrypted biometric data , 2009, Secur. Commun. Networks.

[11]  Emad Taha Khalaf,et al.  Multibiometric systems and template security survey , 2015 .

[12]  M. Gobi,et al.  A Secured Public Key Cryptosystem for Biometric Encryption , 2015 .

[13]  Arun Ross,et al.  A survey on ear biometrics , 2013, CSUR.

[14]  Marina Blanton,et al.  Secure and Efficient Protocols for Iris and Fingerprint Identification , 2011, ESORICS.

[15]  Jan Camenisch,et al.  Privacy and Identity Management for the Future Internet in the Age of Globalisation , 2015, IFIP Advances in Information and Communication Technology.

[16]  K.W. Bowyer,et al.  The Best Bits in an Iris Code , 2009, IEEE Transactions on Pattern Analysis and Machine Intelligence.

[17]  Julien Bringer,et al.  Faster secure computation for biometric identification using filtering , 2012, 2012 5th IAPR International Conference on Biometrics (ICB).

[18]  Yehuda Lindell,et al.  Introduction to Modern Cryptography , 2004 .

[19]  Anoop M. Namboodiri,et al.  Secure hamming distance based biometric authentication , 2013, 2013 International Conference on Biometrics (ICB).

[20]  Mohammed Farik,et al.  Multimodal Authentication - Biometric, Password, And Steganography , 2017 .

[21]  Benny Pinkas,et al.  SCiFI - A System for Secure Face Identification , 2010, 2010 IEEE Symposium on Security and Privacy.

[22]  Jonathan Katz,et al.  Efficient Privacy-Preserving Biometric Identification , 2011, NDSS.

[23]  David Zhang,et al.  An analysis of BioHashing and its variants , 2006, Pattern Recognit..

[24]  Ricardo Dahab,et al.  TinyPBC: Pairings for authenticated identity-based non-interactive key distribution in sensor networks , 2008, 2008 5th International Conference on Networked Sensing Systems.

[25]  Qiang Tang,et al.  An Application of the Goldwasser-Micali Cryptosystem to Biometric Authentication , 2007, ACISP.

[26]  Arjan Kuijper,et al.  Privacy Protection of Biometric Templates , 2014, HCI.