Title: Employing an efficient tamper detection mechanism for IoT-based healthcare systems

Authors: Ahmed A. Elngar

Addresses: Faculty of Science, Al-Azhar Univesity, Cairo, Egypt

Abstract: Security of large-scale networks of internet of things (IoT) is the most significant challenge that needs a smarter security mechanism. Therefore, a tamper detection (TD) is an efficient security mechanism for IoT-based healthcare system, which is used to deal with security violations. Since there are many security threats affect the originality of medical information. In this paper, a new tamper detection mechanism for IoT-based healthcare systems called (IOT-TD) model has been proposed. This paper effectively proposed (ANN-GA) tamper detection mechanism. Where, genetic algorithm (GA) is used to optimise weight and bias values of artificial neural networks (ANN), which lead to maximise the detection accuracy, minimise the timing detection speed and the efficiency energy saving of IoT-network modules. The experimental results showed that the tamper detection performance of (ANN-GA) is 98.51%. In addition, the proposed model showed that the (ANN-GA) enhances the timing detection to 0.03 sec which is important for real-time (IOT-TD) model healthcare system and the efficiency energy saving transmission is 1980 times better than full transmission. Also, the proposed model relies on the certificate-based datagram transport layer security (DTLS) handshake protocol as it is the main security for (IoT-TD) model.

Keywords: internet of things; IoT; tamper detection; healthcare; artificial neural network; genetic algorithm.

DOI: 10.1504/IJITCA.2018.092456

International Journal of Internet of Things and Cyber-Assurance, 2018 Vol.1 No.2, pp.158 - 172

Available online: 08 Jun 2018 *

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