ARTIFICIAL NEURAL NETWORK AND C4.5 ALGORITHMS FOR TAMPER DETECTION MODEL OF HEALTHCARE APPLICATIONS IN INTERNET OF THINGS
yehia, L., Darwish, A., elngar, A., khedr, A. (2017). ARTIFICIAL NEURAL NETWORK AND C4.5 ALGORITHMS FOR TAMPER DETECTION MODEL OF HEALTHCARE APPLICATIONS IN INTERNET OF THINGS. EKB Journal Management System, 17(3), 51-63. doi: 10.21608/ijicis.2017.9148
lobna yehia; ashraf Darwish; Ahmed elngar; Ayman khedr. "ARTIFICIAL NEURAL NETWORK AND C4.5 ALGORITHMS FOR TAMPER DETECTION MODEL OF HEALTHCARE APPLICATIONS IN INTERNET OF THINGS". EKB Journal Management System, 17, 3, 2017, 51-63. doi: 10.21608/ijicis.2017.9148
yehia, L., Darwish, A., elngar, A., khedr, A. (2017). 'ARTIFICIAL NEURAL NETWORK AND C4.5 ALGORITHMS FOR TAMPER DETECTION MODEL OF HEALTHCARE APPLICATIONS IN INTERNET OF THINGS', EKB Journal Management System, 17(3), pp. 51-63. doi: 10.21608/ijicis.2017.9148
yehia, L., Darwish, A., elngar, A., khedr, A. ARTIFICIAL NEURAL NETWORK AND C4.5 ALGORITHMS FOR TAMPER DETECTION MODEL OF HEALTHCARE APPLICATIONS IN INTERNET OF THINGS. EKB Journal Management System, 2017; 17(3): 51-63. doi: 10.21608/ijicis.2017.9148

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

International Journal of Intelligent Computing and Information Sciences
Article 4, Volume 17, Issue 3, July 2017, Page 51-63  XML
Document Type: Original Article
DOI: 10.21608/ijicis.2017.9148
View on SCiNiTO View on SCiNiTO
Authors
lobna yehia1; ashraf Darwish email 1; Ahmed elngar email 2; Ayman khedr email 3
1Computers Science Department Faculty of Science Helwan University, Cairo, Egypt
2Computer Science Department, Al-Alson Higher Institute, Cairo, Egypt
3Information 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.
Keywords
Keywords: Internet of Things (IoT); Tamper detection; security; Healthcare applications; artificial neural network; C4.5 algorithm
Statistics
Article View: 406