As we all know that the biometrics system is used everywhere for person identity verfication. So the biometric system identification is based on the modality and that modalities depends on the physical as well as biological behaviour of the person. The physical behaviour like Fingerprint, Iris, face are. physical behaviour of the human being whereas biological behaviour means according to mannerism of human being are signature or DNA testing of human being . If we are using one modality for identification of person it leads to problem as the modality fail for identification so person has to face problems. If modality fails for identification person comes under problem for that purpose multimodal system is the best option. In multimodal system we are using two modalities for person identification. In this paper we have used two modalities i. e. Fingerprint and Iris. If it is compared with other modalities like palm print, Voice, Fingerprint takes comparative little time for scanning and for saving the files of fingerprint images whereas in Iris identification system user should not be should not be present ,so eye template we can get from anywhere, also two Iris image cannot be identical. In Iris system twins Iris are not identical. We propose our work to fuse the vector of Fingerprint and Iris and that fused method provide security. Template security is the main aim of our analysis. The template should be encrypted and by using that encrypted method template should be protected and it must store in database.

1. P. S. Sanjekar and J. B. Patil, An Overview Of Multimodal Biometrics Department of Computer Engineering, RCPIT, Shirpur ,Signal & Image Processing : An International Journal (SIPIJ) Vol. 4, No. 1, February 2013,DOI :
2. Kulwinder Singh, Kiranbir Kaur, Ashok Sardana,Gulzar Group of Institutes, Khanna, Punjab, India Global Institute of Engineering and Technology, Punjab, India IET Bhaddal, Ropar, Punjab, India,"Fingerprint Feature Extraction", IJCST Vol. 2, Issue 3, September 2011
3. Abhishek Nagar, Student Member, IEEE, Karthik Nandakumar, Member, IEEE, and AnilK. Jain, Fellow, IEEE, Multibiometric Cryptosystems Based on Feature-Level Fusion, IEEE Transactions On Information Forensics And Security, Vol. 7, No. 1, February 2012,Page No255
4. R. N. Kankrale, Prof. S. D. Sapkal. Template Level Fusion of Iris and Fingerprint in Multimodal Biometric Identification Systems, Department of Information Technology SRES
5. A. Jagadeesan, Dr. 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,Vol. 7, No. 2, February 2010
6. Ai-hong Zhu ,Lian Li. Improving for Chaotic Image Encryption Algorithm Based on Logistic Map ,2nd Conference on Environmental Science and Information Application Technology ,2010,Page No:211 -214
7. Sangram Bana1 and Dr. Davinder Kaur2. Fingerprint Recognition using Image Segmentation, Sangram Bana, et al. / (Ijaest) International Journal Of Advanced Engineering Sciences And Technologies Vol No. 5, Issue No. 1, 012 – 023
8. S. Arun Vivek, J. Aravinth, S. Valarmathy Professor "Feature Extraction for Multimodal Biometric and Study of Fusion Using Gaussian Mixture Model".

Cryptosystem Fusion Fuzzy Commitment Fuzzy Vault Selective Encryption.