Abstract: The problem is considered under a global eavesdropper who analyses low level RF transmission attributes, such as the number of transmitted packets, inter-packet times, and traffic directionality, to infer event location, its occurrence time, and the sink location. We devise a general traffic analysis method for inferring contextual information by correlating transmission times with eavesdropping locations. we propose resource-efficient traffic normalization schemes. In comparison to the state-of-the-art, our methods reduce the communication overhead by more than 50%; and the end-to end delay by more than 30%.
Keywords: Wireless Sensor Networks, Sensor Networks, Location Monitoring, eavesdropping.
|
DOI:
10.17148/IJARCCE.2018.784
