New Aadhaar with Multimodal Biometric Model-Based E-Voting System with Dynamic Hybrid IANFIS-PSO
K.Kanimozhi1, K.Thangadurai2

1K.Kanimozhi*, Department of Computer Science, Bharathidasan University, Government Arts College, Karur, India.
2Dr.K.Thangadurai, Department of Computer Science, Bharathidasan University, Government Arts College, Karur, India
Manuscript received on March 15, 2020. | Revised Manuscript received on March 29, 2020. | Manuscript published on April 10, 2020. | PP: 1416-1421 | Volume-9 Issue-6, April 2020. | Retrieval Number: F4529049620/2020©BEIESP | DOI: 10.35940/ijitee.F4529.049620
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Abstract: This work deals with the E-voting system with a biometric concept that will make the voting system smart, secure and easy to vote which can be linked with Aadhaar card. While the process of doing the Aadhaar enrolment process Authorities gathered information of fingerprints and iris of every character and this whole fact of every person persists in the Indian government database. However these two biometric is not enough for the voter authentication process, besides improving the recognition rate, combining multimodal biometric modalities might be more appropriate for E-voting applications. If the Indian Government link this database to the voter ID present in these days vote casting gadget, then all of us can easily forge their votes the use of multimodal biometric authentication. With this motivation, the new Aadhaar with multimodal biometric-based E-voting systems (AMBEVS) system is designed in this work and it allows users to be confirmed using either modality. Here the validation of the voters is verified with the use of Dynamic Hybrid ANFIS-PSO. A critical function and objective of the proposed gadget are to decorate the photograph high-quality and low diploma of complexity for the security of multimodal biometric reputation frameworks. The experimental results show that the proposed AMBEVS are more robust, reliable and accurate as compared to the unimodal based biometric systems. 
Keywords: Aadhaar, Adaptive System of Neuro-fuzzy Inference, Multimodal Biometric Electronic Voting Machine, Optimization of Particle Swarm.
Scope of the Article: Adaptive Systems