Enhancing Wireless Sensor Network Security using Artificial Neural Network based Trust Model

Abstract

Wireless sensor network (WSN) is widely used in environmental conditions where the systems depend on sensing and monitoring approach. Water pollution monitoring system depends on a network of wireless sensing nodes which communicate together depending on a specific topological order. The nodes distributed in a harsh environment to detect the polluted zones within the WSN range based on the sensed data. WSN exposes several malicious attacks as a consequence of its presence in such open environment, so additional techniques are needed alongside with the existing cryptography approach. In this paper an enhanced trust model based on the use of radial base artificial neural network (RBANN) is presented to predict the future behavior of each node based on its weighted direct and indirect behaviors, in order to provide a comprehensive trust model that helps to detect and eliminate malicious nodes within the WSN. The proposed model considered the limited power, storage and processing capabilities of the system.

Authors and Affiliations

Adwan Yasin, Kefaya Sabaneh

Keywords

Related Articles

The Methodology for Ontology Development in Lesson Plan Domain

Ontology has been recognized as a knowledge representation mechanism that supports a semantic web application. The semantic web application that supports lesson plan construction is crucial for teachers to deal with the...

Urdu Text Classification using Majority Voting

Text classification is a tool to assign the predefined categories to the text documents using supervised machine learning algorithms. It has various practical applications like spam detection, sentiment detection, and de...

Variational Formulation of the Template-Based Quasi-Conformal Shape-from-Motion from Laparoscopic Images

One of the current limits of laparosurgery is the absence of a 3D sensing facility for standard monocular laparoscopes. Significant progress has been made to acquire 3D from a single camera using Visual SLAM (Simultaneou...

Increase Efficiency of SURF using RGB Color Space

SURF is one of the most robust local invariant feature descriptors. SURF is implemented mainly for gray images. However, color presents important information in the object description and matching tasks as it clearly in...

An Upper Ontology for Benefits Management of Cloud Computing

Benefits Management provides an established approach for decision making and value extraction for IT/IS investments and, can be used to examine cloud computing investments. The motivation for developing an upper ontology...

Download PDF file
  • EP ID EP90986
  • DOI 10.14569/IJACSA.2016.070932
  • Views 92
  • Downloads 0

How To Cite

Adwan Yasin, Kefaya Sabaneh (2016). Enhancing Wireless Sensor Network Security using Artificial Neural Network based Trust Model. International Journal of Advanced Computer Science & Applications, 7(9), 222-228. https://europub.co.uk/articles/-A-90986