DocumentCode :
3343041
Title :
Towards Statistically Strong Source Anonymity for Sensor Networks
Author :
Min Shao ; Yi Yang ; Sencun Zhu ; Guohong Cao
Author_Institution :
Pennsylvania State Univ., University Park, PA
fYear :
2008
fDate :
13-18 April 2008
Abstract :
For sensor networks deployed to monitor and report real events, event source anonymity is an attractive and critical security property, which unfortunately is also very difficult and expensive to achieve. This is not only because adversaries may attack against sensor source privacy through traffic analysis, but also because sensor networks are very limited in resources. As such, a practical tradeoff between security and performance is desirable. In this paper, for the first time we propose the notion of statistically strong source anonymity, under a challenging attack model where a global attacker is able to monitor the traffic in the entire network. We propose a scheme called FitProbRate, which realizes statistically strong source anonymity for sensor networks. We also demonstrate the robustness of our scheme under various statistical tests that might be employed by the attacker to detect real events. Our analysis and simulation results show that our scheme, besides providing source anonymity, can significantly reduce real event reporting latency compared to two baseline schemes.
Keywords :
statistical testing; telecommunication network management; telecommunication security; telecommunication traffic; wireless sensor networks; FitProbRate; attack model; event source anonymity; sensor networks; sensor source privacy; statistical test; statistically strong source anonymity; traffic analysis; traffic monitoring; Analytical models; Delay; Discrete event simulation; Event detection; Monitoring; Privacy; Robustness; Telecommunication traffic; Testing; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
INFOCOM 2008. The 27th Conference on Computer Communications. IEEE
Conference_Location :
Phoenix, AZ
ISSN :
0743-166X
Print_ISBN :
978-1-4244-2025-4
Type :
conf
DOI :
10.1109/INFOCOM.2008.19
Filename :
4509614
Link To Document :
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