ACM Home Page
Please provide us with feedback. Feedback
Towards event source unobservability with minimum network traffic in sensor networks
Full text PdfPdf (345 KB)
Source
Conference On Wireless Network Security archive
Proceedings of the first ACM conference on Wireless network security table of contents
Alexandria, VA, USA
SESSION: Sensor network security table of contents
Pages 77-88  
Year of Publication: 2008
ISBN:978-1-59593-814-5
Authors
Yi Yang  The Pennsylvania State University, University Park, PA
Min Shao  The Pennsylvania State University, University Park, PA
Sencun Zhu  The Pennsylvania State University, University Park, PA
Bhuvan Urgaonkar  The Pennsylvania State University, University Park, PA
Guohong Cao  The Pennsylvania State University, University Park, PA
Sponsors
SIGSAC: ACM Special Interest Group on Security, Audit, and Control
ACM: Association for Computing Machinery
Publisher
ACM  New York, NY, USA
Bibliometrics
Downloads (6 Weeks): 7,   Downloads (12 Months): 139,   Citation Count: 4
Additional Information:

abstract   references   cited by   index terms   collaborative colleagues  

Tools and Actions: Request Permissions Request Permissions    Review this Article  
DOI Bookmark: Use this link to bookmark this Article: http://doi.acm.org/10.1145/1352533.1352547
What is a DOI?

ABSTRACT

Sensors deployed to monitor the surrounding environment report such information as event type, location, and time when a real event of interest is detected. An adversary may identify the real event source through eavesdropping and traffic analysis. Previous work has studied the source location privacy problem under a local adversary model. In this work, we aim to provide a stronger notion: event source unobservability, which promises that a global adversary cannot know whether a real event has ever occurred even if he is capable of collecting and analyzing all the messages in the network at all the time. Clearly, event source unobservability is a desirable and critical security property for event monitoring applications, but unfortunately it is also very difficult and expensive to achieve for resource-constrained sensor network.

Our main idea is to introduce carefully chosen dummy traffic to hide the real event sources in combination with mechanisms to drop dummy messages to prevent explosion of network traffic. To achieve the latter, we select some sensors as proxies that proactively filter dummy messages on their way to the base station. Since the problem of optimal proxy placement is NP-hard, we employ local search heuristics. We propose two schemes (i) Proxy-based Filtering Scheme (PFS) and (ii) Tree-based Filtering Scheme (TFS) to accurately locate proxies. Simulation results show that our schemes not only quickly find nearly optimal proxy placement, but also significantly reduce message overhead and improve message delivery ratio. A prototype of our scheme was implemented for TinyOS-based Mica2 motes.


REFERENCES

Note: OCR errors may be found in this Reference List extracted from the full text article. ACM has opted to expose the complete List rather than only correct and linked references.

 
1
Csim 19, http://www.mesquite.com/.
 
2
Glomosim, http://pcl.cs.ucla.edu/projects/glomosim/.
 
3
Mica2 mote, http://www.xbow.com/.
 
4
TinyOS. http://www.tinyos.net.
 
5
Anonymity bibliography, http://freehaven.net/anonbib/date.html, 2005.
6
 
7
8
 
9
 
10
C. Díaz and B. Preneel. Taxonomy of mixes and dummy traffic. In Proceedings of I-NetSec04: 3rd Working Conference on Privacy and Anonymity in Networked and Distributed Systems, 2004.
 
11
S. Fischer-Hubner. Privacy Enhancing Technologies, volume 1958. Springer Berlin Heidelberg, 2001.
 
12
 
13
 
14
15
 
16
 
17
18
 
19
 
20
W. Zhang, M. Tran, S. Zhu, and G. Cao. A Compromise-Resilient Scheme for Pairwise Key Establishment in Dynamic Sensor Networks. In ACM Mobihoc, 2007.
 
21
 
22
K. Mehta, D. Liu, and M. Wright. Location privacy in sensor networks against a global eavesdropper. In ICNP, 2007.
 
23
U. Möller, L. Cottrell, P. Palfrader, and L. Sassaman. Mixmaster Protocol - Version 2. Draft, July 2003.
24
 
25
 
26
S. Ratnasamy, D. Estrin, R. Govindan, B. Karp, L. Yin, S. Shenker, and F. Yu. Data-centric storage in sensornets. In Proceedings of ACM First Workshop on Hot Topics in Networks, 2001.
 
27
M. Shao, S. Zhu, W. Zhang, and G. Cao. pDCS: Security and privacy support for data-centric sensor networks. In IEEE INFOCOM, 2007.
 
28
M. Shao, Y. Yang, S. Zhu, and G. Cao. Towards Statistically Strong Source Anonymity for Sensor Networks. In IEEE INFOCOM, 2008.
29
 
30
Y. Xi, L. Schwiebert, and W. Shi. Preserving source location privacy in monitoring-based wireless sensor networks. In SSN '06.
 
31
Y. Zhang, W. Liu, , and W. Lou. Anonymous communications in mobile ad hoc networks. In IEEE INFOCOM, 2005.
 
32
 
33


Collaborative Colleagues:
Yi Yang: colleagues
Min Shao: colleagues
Sencun Zhu: colleagues
Bhuvan Urgaonkar: colleagues
Guohong Cao: colleagues