Towards event source unobservability with minimum network traffic in sensor networks
WiSec '08 Proceedings of the first ACM conference on Wireless network security
PEON: privacy-enhanced opportunistic networks with applications in assistive environments
Proceedings of the 2nd International Conference on PErvasive Technologies Related to Assistive Environments
Compromising anonymous communication systems using blind source separation
ACM Transactions on Information and System Security (TISSEC)
Maelstrom: receiver-location preserving in wireless sensor networks
WASA'11 Proceedings of the 6th international conference on Wireless algorithms, systems, and applications
Security and Communication Networks
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We propose a methodology to identify nodes in fully anonymizedwireless networks using collections of very simple sensors. Based on time series of counts of anonymous packets provided by the sensors, we estimate the number 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 available sensors, 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 anonymized TCP traffic. Additional experiments indicate that the estimators perform very well in anonymous wireless networks that use traffic padding.