Detection of Security Attacks in Wireless Sensor Networks

Abstract

One of the primary concerns in sensor networks is Security. Wireless Sensor Network involves a considerable number of nodes which can be known as” tiny sensor nodes”. These nodes swap the information with other nodes by special wireless links in a short period. The information is perhaps private for many people or business dealings. These networks are exposed to many attackers due to deployment in distant areas and distributed behavior. At the sensor node level, the networks are controlled by different constraints like less memory capacity, low transmission range, and less battery power. Where at the network level, they are controlled by irregular connectivity and Adhoc networking. This research may analyze the main security issues, security breaches, and challenges in the Wireless Sensor Networks world based on the analysis of Low Energy Adaptive Clustering Hierarchy (LEACH), Which is a cluster-based routing protocol by varying the number of clusters to observe the effect on Sensor Network performance in terms of network lifetime, energy dissipation, and amount of data reaching the base station. A scheme has been proposed for collecting and processing the data and then producing 12 features. This ordered dataset is called Wireless Sensor Networks- Data Set (WSN-DS). Support Vector Machine (SVM) was trained on the dataset for detecting and classifying the DoS attacks where 80% for training and 20% for testing. The results section shows how the WSN DS increased the capability of the Intrusion Detection System (IDS) to realize a better classification accuracy rate. The classification accuracies of attacks were 100%, and 98% for Normal, Black hole, and Sinkhole attacks.

Keywords

Support vector machine (SVM), DDos, Blackhole, Sinkhole, Low-Energy Adaptive Clustering Hierarchy (LEACH) Protocol, Wireless Sensor Networks (WSN)

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About Authors

Sura Alsharifi is an M.Sc. student in Computer Science at the University of Mosul / Iraq. She can be contacted at email: sura.20csp80@student.uomosul.edu.iq

Mafaz Alanezi is a faculty member at the Department of Computer Science, University of Mosul, Iraq. She obtained her Ph.D. degree in Computer Science in the field of Computer and Network Security from University of Mosul / Iraq in 2012. Her M.Sc. degree was also in Computer Science in the field of Image Processing from the University of Mosul/ Iraq in 2003. Her current scientific degree Prof. Dr in Cybersecurity and Information Security. She can be contacted at email: mafazmhalanezi@uomosul.edu.iq