CFP last date
20 May 2024
Reseach Article

Fingerprint bio-Crypto key generation using Scale Invariant Feature Transform (SIFT)

by S. Partheeba, N. Radha
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 153 - Number 8
Year of Publication: 2016
Authors: S. Partheeba, N. Radha
10.5120/ijca2016912129

S. Partheeba, N. Radha . Fingerprint bio-Crypto key generation using Scale Invariant Feature Transform (SIFT). International Journal of Computer Applications. 153, 8 ( Nov 2016), 35-41. DOI=10.5120/ijca2016912129

@article{ 10.5120/ijca2016912129,
author = { S. Partheeba, N. Radha },
title = { Fingerprint bio-Crypto key generation using Scale Invariant Feature Transform (SIFT) },
journal = { International Journal of Computer Applications },
issue_date = { Nov 2016 },
volume = { 153 },
number = { 8 },
month = { Nov },
year = { 2016 },
issn = { 0975-8887 },
pages = { 35-41 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume153/number8/26426-2016912129/ },
doi = { 10.5120/ijca2016912129 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-06T23:58:37.615428+05:30
%A S. Partheeba
%A N. Radha
%T Fingerprint bio-Crypto key generation using Scale Invariant Feature Transform (SIFT)
%J International Journal of Computer Applications
%@ 0975-8887
%V 153
%N 8
%P 35-41
%D 2016
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Network security has become a great threat to the network accessible resources that consists of policies to prevent, monitor unauthorized access, modification, and misuse of computer network. Several algorithms and techniques were proposed for the secure transmission of data and to protect user’s privacy. Secret-key cryptography and public-key cryptography are the techniques used for the protection of security issues. However, such a key needs to be stored in a protected place or it should be transported by a shared communication line. So generation of cryptographic key using biometric traits of both sender and receiver during communication avoids key storing and improves security strength. The proposed approach for detecting the quality of fingerprint by using the method called orientation certainty level (OCL). If the image has good quality then feature extraction will be done using Scale Invariant Feature Transform, otherwise poor quality image will get ignored. By using cover image the obtained cancellable template will get hidden. Then the hidden image will be transmitted from sender to receiver and receiver to receiver to sender by using Variable Least Significant Bit techniques. Finally the performance metrics like FAR (False Acceptance Rate), FRR (False Rejection Rate), and Accuracy of the proposed work is compared with the existing system.

References
  1. A. Jagadeesan, K. Duraiswamy “Secured Cryptographic Key Generation from Multimodal Biometrics: Feature Level Fusion of Fingerprint and Iris”, (IJCSIS) International Journal of Computer Science and Information Security, 7(2), No.2, 2010.
  2. Sunil V. K. Gaddam, Manohar Lal, “Efficient Cancellable Biometric Key Generation Scheme for Cryptography”, International Journal of Network Security, 11(9), PP.61-69, No.2, 2010.
  3. M.S. Durairajan, Dr.R.Saravanan, “Biometrics based key generation using Diffie Hellman Key Exchange for enhanced security Mechanism”, International Journal of Chem Tech Research, 6(9), PP.4359-4365, No.9, 2014.
  4. B.Raja Rao, Dr.E.V.V.Krishna Rao, S.V.Rama Rao, M.Rama mohan rao, “Fingerprint Parameter Based Cryptographic Key Generation”, International Journal of Engineering Research and Applications(IJERA), 2(12), PP.1598-1604, Issue 6, 2012. ISSN:2248-9622.
  5. Mr.P.Balakumar, Dr.R.Venkatesan, “Secure Biometric Key Generation Scheme for Cryptography using Combined Biometric Features of Fingerprint and Iris”, International Journal of computer science Issues(IJCSI), 8(9), Issue 5, No.2,2011. ISSN:1694-0814.
  6. Muthkumar Arunachalam, Kannan Subramanian, “AES Based Multimodal Biometric Authentication using Cryptography Biometric Features of Fingerprint and Iris”,The International Arab Journal of Information Technology “,12(9), No.5, 2015.
  7. Barman, S., Samanta, D., & Chattopadhyay, S. (2015).” Fingerprint-based crypto-biometric system for network security”.  EURASIP Journal on Information Security, no.1, pp.1-17, 2015.
  8. N.Lalithamani, Dr.K.P.Soman, “An Effective Scheme for Generating Irrevocable cryptographic key from Cancelable Fingerprint Templates”, International journal of Computer Science and Network security(IJCSNS), 9(3), No.3, 2009.
  9. Deepika Sahu, Rashmi Shrivas, “Minutaie Based Fingerprint Matching for Identification and Verification”, International journal of science and Research(IJSR), 5(3), Issue.3, 2016. ISSN:2319-7064
  10. A.Jagadeesan, T.Thillaikkarasi, Dr.K.Duraiswamy, “ Cryptographic Key Generation from Multiple Biometric Modalities:Fusing Minutiae with Iris Feature”, International Journal of Computer Applications, 2(6), No.6, 2010
  11. K.Hemanth, Srinivasulu Asadi, Dabbu Murali, N.Karimulla, M.Aswin, “ High Secure Crypto Biomertic Authentication Protocol”, International Journal of Computer Scince and Information Technologies, Vol.2, No.6, PP.2496-2502, 2011. ISSN: 0975-9646
  12. R.Divya, V.Vijayalakshmi, “Analysis of Multimodal Fusion Based Authentication Techniques for Network”, International Journal of Security and its Applications, Vol.9, No.4, PP.236-246, 2015.
  13. Nalini.P, “SIFI Based Minutia Descriptors for Fingerprint Combination Protection”, International Journal of Science, Engineering and Technology Research(IJSETR), 4(11), Issue 11, 2015.
  14. N.Lalithamani, Dr.K.P.Soman, “Towards Generating Irrevocable Key for Cryptography from Cancelable Fingerprints”, IEEE.2009.
  15. Ravi K Sheth, Sarika P.Patel, “Analysis of Cryptography Techniques”, International Journal of Research in Advance Engineering, 1(2), Issue.2, 2015.
  16. Arunprakash.K, Narayanan R.C, Dr. Krishnamoorthy .K,” Reduction of false Acceptance Rate using Cross Validation for Fingerprint Recognition biometric System” International journal for trends in Engineering and technology,3(1), Issue.1, 2015
  17. Manvjeet Kaur, Mukhwinder Singh, Akshay Girdhar, Parvinder S. Sandhu, “ Fingerprint Verification System using Minutiae Extraction Technique”, International Journal of Computer, Electrical, Automation, Control and information Engineering, vol.2, No.10, 2008.
  18. V. Lokeswara Reddy, Dr. A. Subramanyam, Dr. P. Chenna Reddy, “ Implementation of LSB Steganography and its evaluation for various file formats”, International journal of Advanced Networking and Applications, vol.2, Issue.5, Pages:868-872(2011).
  19. Janani. B, Dr.N. Radha, “Cancelable Template Generation Based on Improved Quality Fingerprint for Person Authentication”, International journal of engineering and computer science, vol. 4(1), Issue.1,PP:9892-9898,2015. ISSN:2319-7242.
  20. Ms.S.Malathi, Dr.C.Meena, “Partial Fingerprint matching based on SIFI Features”, International Journal on Computer Science and Engineering(IJCSE), Vol.02, No.04, PP.1411-1414, 2010.
Index Terms

Computer Science
Information Sciences

Keywords

Cryptography key Orientation Certainty Level Scale Invariant Feature Transform Variable Least Significant Bit