Simulation of Biometric Data in VANETs using Layer Recurrent Model
Ekta Narwal1, Sumeet Gill2
1Ekta Narwal*, Department of Mathematics, Maharshi Dayanad University, Rohtak. India.
2Sumeet Gill, Department of Mathematics, Maharshi Dayanad University, Rohtak. India. 

Manuscript received on November 12, 2019. | Revised Manuscript received on November 25, 2019. | Manuscript published on 30 November, 2019. | PP: 4715-4718 | Volume-8 Issue-4, November 2019. | Retrieval Number: D8578118419/2019©BEIESP | DOI: 10.35940/ijrte.D8578.118419

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Abstract: Biometric identification methods like fingerprints are used throughout the world for authentication such methods are now being researched worldwide for VANETs too. Normally such data are stored in respective files in a computer machine but normally such data from servers/computers are crack-able. There is a need of improving security of such data from intruders as this data contains private information of the driver on road. In this paper we proposed to design and simulate the storage of such biometric data in the form of network parameters of a Neural Network. The simulation of the network is done by using recurrent model and the parameters are saved in place of original biometric images which makes the images impossible to crack. There by providing much more security to the biometric data.
Keywords: VANET, Biometric, Fingerprints, Recurrent Neural Network, Artificial Neural Network.
Scope of the Article: Application Artificial Intelligence and machine learning in the Field of Network and Database.