An Efficient and Secured Biometric Authentication for IoT

Abstract

The Internet of Things (IoT) is that the ability to produce everyday devices with the way of identification and otherwise for communication with one nother. The spectrum of IoT application domains is extremely massive together with sensible homes, sensible cities, wearable's, e-health, etc. Consequently, tens and even many billions of devices are going to be connected. Such devices can have sensible capabilities to gather, analyze and even create selections with none human interaction. Security may be a supreme demand in such circumstances, associated specially authentication is of high interest given the injury that might happen from a malicious unauthenticated device in an IoT system. Fingerprint based mostly biometry authentication approaches can enhance the protection in several industries and endless applications reminiscent of police work, automotive business, sensible town development, sensible home etc. This paper presents the fingerprint {based mostly primarily based mostly} identification for breakdown the protection challenges in IoT based applications.

Dactylogram Based Voting System Using Image Encryption and Symmetric Key Encryption

“…The content involved in the process is that the voting system with the dactylogram (i.e. ).The fingerprint [22] of each user is captured and then the obtained image is stored in the dataset where all the images of the fingerprint of the user are stored. These images are then encrypted Encrypt (image [I]) where I represents each user, the encryption algorithm preferred is Triple DES algorithm using three keys.…”

Cloud data Search and verification using Order Preserving Encryption

“…We tend to win this aim by exploiting and unambiguously combining techniques of attribute-based secret writing. [29][30][31][32][33]…”

Design and Development of IoT based Intelligent Home Automation System

“…Not only can cloud store that data efficiently but it can use cloud computing to decrease the hardware and software demand form the user. This allows for a system with weak processor of Raspberry Pi to perform deep learning tasks as facial recognition [11] [12].…”