Con dentiality In Sensor Networks : Transactional Information

In a sensor network environment, elements such as message rate, message size, mote frequency, and message routing can reveal information about the sensors deployed, frequency of events monitored, network topology, parties deploying the network, and location of subjects and objects moving through the networked space. Collectively, we refer to these elements as transactional data. Where the con dentiality of the content of the networks communications has been secured through encryption and authentication techniques, the ability of network outsiders and insiders to observe elements or the totality of this transactional data can also compromise network con dentiality. This paper describes four types of transactional data typically observable in sensor networks and discusses the information that can be derived through its observation and analysis. The paper argues that measures to limit the availability and utility of transactional data are essential to preserving con dentiality in sensor networks.

[1]  Gaetano Borriello,et al.  Location Systems for Ubiquitous Computing , 2001, Computer.

[2]  Peter Thomson,et al.  Real-time health monitoring of civil infrastructure systems in Colombia , 2001, SPIE Smart Structures and Materials + Nondestructive Evaluation and Health Monitoring.

[3]  John Anderson,et al.  Wireless sensor networks for habitat monitoring , 2002, WSNA '02.

[4]  Orin S. Kerr A User's Guide to the Stored Communications Act, and a Legislator's Guide to Amending it , 2003 .

[5]  Tarek F. Abdelzaher,et al.  AIDA: Adaptive application-independent data aggregation in wireless sensor networks , 2004, TECS.

[6]  Deborah Estrin,et al.  Habitat monitoring with sensor networks , 2004, CACM.

[7]  Stephan Olariu,et al.  On providing anonymity in wireless sensor networks , 2004, Proceedings. Tenth International Conference on Parallel and Distributed Systems, 2004. ICPADS 2004..

[8]  Deirdre K. Mulligan,et al.  Reasonable Expectations in Electronic Communications: A Critical Perspective on the Electronic Communications Privacy Act , 2004 .

[9]  Dongxi Liu,et al.  Normalizing traffic pattern with anonymity for mission critical applications , 2004, 37th Annual Simulation Symposium, 2004. Proceedings..

[10]  Liang Zhang,et al.  Organizational memory: reducing source-sink distance , 1997, Proceedings of the Thirtieth Hawaii International Conference on System Sciences.

[11]  John A. Stankovic,et al.  ALARM-NET: Wireless Sensor Networks for Assisted-Living and Residential Monitoring , 2006 .

[12]  Yurong Xu,et al.  Providing Anonymity in Wireless Sensor Networks , 2007, IEEE International Conference on Pervasive Services.

[13]  Wenyuan Xu,et al.  Temporal Privacy in Wireless Sensor Networks , 2007, 27th International Conference on Distributed Computing Systems (ICDCS '07).