ARTIFICIAL NEURAL NETWORK AND C4.5 ALGORITHMS FOR TAMPER DETECTION MODEL OF HEALTHCARE APPLICATIONS IN INTERNET OF THINGS

Document Type : Original Article

Authors

1 Computers Science Department Faculty of Science Helwan University, Cairo, Egypt

2 Computer Science Department, Al-Alson Higher Institute, Cairo, Egypt

3 Information Systems Department, Faculty of Computers & Information, Helwan University, Cairo, Egypt

Abstract

Abstract: Security of a network is the most important challenges of the Internet of Things (IOT) that needs smarter security mechanism. Tamper detection is an effective technique used to deal with security violations. In this paper, a new IoT-Tamper Detection Model (TDM) based IoT for real data of healthcare applications has been proposed. In this model, artificial neural network (ANN) algorithm with RC4-EA encryption method and IOT-C4.5 algorithm are applied for TDM. The experimental results showed that the detection performance of ANN is 98.51% and 76.66 % for the C4.5 algorithm. In addition, the proposed model showed that the ANN algorithm enhances the timing speed than C4.5 algorithm which is important for real time IOT - TDM healthcare application.

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