Measuring the impact of denial-of-service attacks on wireless sensor networks

Abstract

Wireless sensor networks (WSNs) are especially susceptible to denial-of-service attacks due to the resource-constrained nature of motes. We follow a systematic approach to analyze the impacts of these attacks on the network behavior; therefore, we first identify a large number of metrics easily obtained and calculated without incurring too much overhead. Next, we statistically test these metrics to assess whether they exhibit significantly different values under attack when compared to those of the baseline operation. The metrics look into different aspects of the motes and the network, for example, MCU and radio activities, network traffic statistics, and routing related information. Then, to show the applicability of the metrics to different WSNs, we vary several parameters, such as traffic intensity and transmission power. We consider the most common topologies in wireless sensor networks such as central data collection and meshed multi-hop networks by using the collection tree and the mesh protocol. Finally, the metrics are grouped according to their capability of distinction into different classes. In this work, we focus on jamming and blackhole attacks. Our experiments reveal that certain metrics are able to detect a jamming attack on all motes in the testbed, irrespective of the parameter combination, and at the highest significance value. To illustrate these facts, we use a standard testbed consisting of the widely-employed TelosB motes.