Nabila Rahman

Graduation Semester and Year




Document Type


Degree Name

Master of Science in Computer Science


Computer Science and Engineering

First Advisor

Matthew Wright


Wireless sensor networks (WSNs) have great practical importance for surveillance systems to perform monitoring by acquiring and sending information about intrusions into a secured area. Very little human intervention is required for WSNs, which is one of the most desirable features of them and thus making them a cheaper and safer alternative for securing large area such as international borders. Jamming attacks in WSNs can be applied to disrupt communications among the sensor nodes in the network by barring the reception of wireless signals of the sensor nodes' transceivers. Since it is difficult to prevent jamming attacks, detection and mapping out the jammed regions is critical to overcome this problem. In a security monitoring scenario, the network operator will be able to take proper measures against jamming once the jammed regions in the network are known to them. It is also desirable to keep the interactions of the sensor nodes in the network minimal, as they are low-powered devices and need to conserve their resources. In this paper, we propose a light-weight technique for faster mapping of the jammed regions. We minimize the load on the sensors by removing the actual responsibility of mapping from the network to a central base station (BS). After a few nodes report to the BS, it carries out the task of mapping of the jammed regions in the network. We use our simulation results to compare our proposed system with the existing techniques and also to measure the performance of our system. Our results show that the jammed regions in a network can be mapped from just a few nodes reporting to the base station. We used our results to measure the speed, overhead and accuracy of mapping by varying different parameters of the network. Also, we tested with real sensor nodes in the presence of a jamming sensor to experiment with jammed regions and map them using our proposed system.


Computer Sciences | Physical Sciences and Mathematics


Degree granted by The University of Texas at Arlington