An efficient security system based on cancelable face recognition with blockchain over cognitive IoT
Pages 44741 - 44761
Abstract
This paper presents a new authentication framework for cancelable face recognition biometrics. In recent years, biometric plays a pivotal role in Cognitive Internet of Things (C-IoT) security. The face trait solves a lot of security issues; it increases the resistance of these systems against severe authentication attacks especially in smart IoT-based applications. The proposed scheme runs in two phases; The first phase (enrollment), in which the face image of the person is hashed using SHA256, is passed to an algorithm to extract the main features. Then the image is decomposed using a wavelet transform algorithm. Wavelet transform is applied to hide the face details from the image. This step is done to protect the image against being stolen or modified by external hackers. The image, hash, and wavelet transform are passed through the raspberry Pi to be stored in a database. A block is added to the private blockchain with these files. In the second phase (authentication) the test image is hashed, passed to the system to extract the features, and compared with the stored images in the database. Then the decision is stored in a new block in the chain, whether the two images are identical or not. The simulation results based demonstrate that the proposed cancelable biometric system gives a very reliable and secure performance for securing the IoT applications.
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© The Author(s), under exclusive licence to Springer Science+Business Media, LLC, part of Springer Nature 2023. Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.
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Kluwer Academic Publishers
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Publication History
Published: 02 May 2023
Accepted: 19 April 2023
Revision received: 28 December 2021
Received: 26 August 2021
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