Abstract

We propose two algorithms to estimate the number and location of nodes in a fully anonymized wireless network using a network of very simple sensors. Based on time series of counts of anonymous packets provided by the sensors, we estimate the density of nodes using Principal Component Analysis. We then proceed to separate the collected packet data into traffic flows that, with help of the spatial diversity in the sensor network, can be used to estimate the location of the wireless nodes. Our simulation experiments indicate that the estimators show high accuracy and high confidence for TCP traffic. Addition experiments indicate that the estimators perform very well in wireless networks that use traffic padding to prevent anonymity attacks. Based on these results, we believe that a new MAC protocol that considers both privacy and efficient use of bandwidth is needed. 1

Citations