Detection of Identity-Based Attacks in Wireless Sensor Networks Using Signalprints

A number of green technologies such as Smart Power Grids, Smart Buildings, Smart Industrial Process and Smart Transportation rely on sensor technology. Sensor networks consist of a network of autonomous sensors that can reconfigure themselves so as to sense the environment in the most efficient manner. However, a significant challenge in the practical application of sensor networks is the need for credible network security. An important problem in wireless network security is sender authentication. The existing schemes for sender authentication that are based on IP and MAC address can be easily spoofed by the sender. In this paper, we propose a method to apply signal prints to WSNs so as to detect identity-based attacks. The use of signal prints allows us to identify the sender based on the received signal characteristics thereby making it harder to spoof. However, in a Wireless Sensor Network (WSN), battery discharge causes received signal characteristics to vary. Also, WSNs are dense networks and, generally, do not have a centralized authority. These must be taken into a consideration while designing a solution.