  We propose an efficient scheme for generating fake network traffic to
disguise the real event notification in the presence of a global eavesdropper,
which is especially relevant for the quality of service in delay-intolerant
applications monitoring rare and spatially sparse events, and deployed as large
wireless sensor networks with single data collector. The efficiency of the
scheme that provides statistical source anonymity is achieved by partitioning
network nodes randomly into several node groups. Members of the same group
collectively emulate both temporal and spatial distribution of the event. Under
such dummy-traffic framework of the source anonymity protection, we aim to
better model the global eavesdropper, especially her way of using statistical
tests to detect the real event, and to present the quality of the location
protection as relative to the adversary's strength. In addition, our approach
aims to reduce the per-event work spent to generate the fake traffic while,
most importantly, providing a guaranteed latency in reporting the event. The
latency is controlled by decoupling the routing from the fake traffic schedule.
We believe that the proposed source anonymity protection strategy, and the
quality evaluation framework, are well justified by the abundance of the
applications that monitor a rare event with known temporal statistics, and
uniform spatial distribution.
