A Realtime Adaptive Trust Model Based on Artificial Neural Networks for Wireless Sensor Networks

Authors

  • Khaled Mohammed Ali Hassan Al-Azhar University, Faculty of Engineering, Computers and Systems Engineering Department, Cairo, Egypt
  • Mohamed Ashraf Madkour Al-Azhar University, Faculty of Engineering, Computers and Systems Engineering Department, Cairo, Egypt
  • Sayed Abd El Hady Nouh Al-Azhar University, Faculty of Engineering, Computers and Systems Engineering Department, Cairo, Egypt

DOI:

https://doi.org/10.13052/jcsm2245-1439.1244

Keywords:

WSNs, trust and reputation management models, ATSR, ML, ANN, backpropagation algorithm, routing cost function (RCF), internal attacks

Abstract

Wireless sensor networks (WSNs) are vulnerable to security attacks due to the unbounded nature of the wireless medium, restricted node resources, and cooperative routing. Standard cryptography and authentication mechanisms help protect against external attacks, but a compromised node can easily bypass them. This work aims to protect WSNs against internal attacks, which are mostly launched from compromised nodes to disrupt the network’s operation and/or reduce its performance. The trust and reputation management framework provides a routing cost function for selecting the best secure next hop. Tuning the trust weights is essential to cope with the constant changes in the network environment, such as the sensor nodes’ behaviours and locations. To allow real-time operation, the proposed framework introduces an artificial neural network (ANN) in each sensor node that automatically adjusts the weights of the considered trust metrics according to the WSN state. A large dataset is generated to train and test the ANN using a multitude of simulated cases. A prototype is developed and tested using the J-Sim simulator to show the performance gain resulting from applying the adaptive trust model. The experimental results showed that the adaptive model has robust performance and has achieved an improved packet delivery ratio with reduced power consumption and reduced average packet loss. The results showed that when sensor nodes were static and malicious nodes were present, the average accuracy was 99.6%, while when they were in motion, it was 88.1%.

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Author Biographies

Khaled Mohammed Ali Hassan, Al-Azhar University, Faculty of Engineering, Computers and Systems Engineering Department, Cairo, Egypt

Khaled Mohammed Ali Hassan has received a bachelor’s degree in Computer Engineering from the Electronics and Electricity Faculty of Engineering at Aleppo University in Syria. He received his master’s degree in Computer Engineering from the Faculty of Engineering at Cairo University in 2015. He is currently working as a researcher on his Ph.D. in the Systems and Computers Engineering Department of the Faculty of Engineering at Al-Azhar University in Cairo, Egypt.

Mohamed Ashraf Madkour, Al-Azhar University, Faculty of Engineering, Computers and Systems Engineering Department, Cairo, Egypt

Mohamed Ashraf Madkour has got his B. Sc. and M. Sc., degrees in Electrical Engineering in 1968 and 1974, respectively, and got his Ph. D. degree in computer networking from the Electrical Engineering Department, Ain Shams University in 1981. Dr. Madkour is a professor emeritus in the Systems and Computers Engineering Department, Faculty of Engineering, Al-Azhar University, Cairo, Egypt, where he teaches courses and does research on computer networking, internetworking, and systems and data security. Dr. Madkour has published more than 40 research papers in international and local journals and conferences, and his research interests include internetworking and wireless networks, cyber security, artificial intelligence, and data science.

Sayed Abd El Hady Nouh, Al-Azhar University, Faculty of Engineering, Computers and Systems Engineering Department, Cairo, Egypt

Sayed Abd El Hady Nouh is a computer network professor in the Department of Computers and Systems Engineering at Al-Azhar University in Cairo, Egypt. He received his B.Sc. degree in Communications Engineering and his M.Sc. degree in Computer Engineering from Al-Azhar University in 1978 and 1982, respectively. He received his Ph.D. degree in Computer Engineering from AGH University, Cracov, Poland, in 1992. From 2006–2010, he served as the Egyptian Consultant at the African Union, in Addis Ababa, Ethiopia. From 2012 to 2015, he served as the chairman of the Computers and Systems Engineering Department at Al-Azhar University. He is the chairman of the committee for upgrading professors and associate professors. He has been an IEEE member since 1991. He has been involved with research in performance analysis and evaluation of computer networks, Ad-hoc routing protocols, routing and security protocols for wireless sensor networks, mobile computing and wireless networking, modeling and computer simulation techniques, and data communications networks.

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Published

2023-06-30

How to Cite

1.
Hassan KMA, Madkour MA, Nouh SAEH. A Realtime Adaptive Trust Model Based on Artificial Neural Networks for Wireless Sensor Networks. JCSANDM [Internet]. 2023 Jun. 30 [cited 2025 Feb. 16];12(04):519-46. Available from: https://journals.riverpublishers.com/index.php/JCSANDM/article/view/19103

Issue

2023: Vol 12 Iss 4

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Articles

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