NetSANI (network trace sanitization) project (2009-2012)

This project is no longer active; this page is no longer updated.

• Summary
• People
• Funding
• Papers

Related projects: [CRAWDAD], [DIST], [MAP], [Wi-Fi-measurement]

Related keywords: [data], [privacy], [wifi]

Summary

The NetSANI (Network Trace Sanitization and ANonymization Infrastructure) project aimed to increase network-trace sharing by making it safer and easier to sanitize network traces (remove sensitive information). Sanitization always involves a challenging trade-off between sanitization effectiveness (providing anonymity for network users and secrecy for network operational information) and research usefulness (since only the information retained can be used by the researcher).

To this end, the NetSANI goal was to be a flexible and extensible suite of software tools for sanitizing network traces, based on user-specified sanitization goals and user-specified research goals. We never quite achieved that goal, but we conducted some anonymization (and de-anonymization) research.

People

Keren Tan, Chris McDonald, Jihwang Yeo, Phil Fazio, Guanhua Yan, and David Kotz.

Funding

Funded by the National Science Foundation (NSF) Cyber Trust Award CNS-0831409.

The views and conclusions contained on this site and in its documents are those of the authors and should not be interpreted as necessarily representing the official position or policies, either expressed or implied, of the sponsor(s). Any mention of specific companies or products does not imply any endorsement by the authors or by the sponsor(s).

Papers (tagged 'netsani')

[Also available in BibTeX]

Papers are listed in reverse-chronological order. Follow updates with RSS.

2012:

• Phillip A. Fazio, Keren Tan, and David Kotz. Effects of network trace sampling methods on privacy and utility metrics. Proceedings of the Annual Workshop on Wireless Systems: Advanced Research and Development (WISARD), pages 1–8. IEEE, January 2012. doi:10.1109/COMSNETS.2012.6151387. [Details]

2011:

• Keren Tan. Large-scale Wireless Local-area Network Measurement and Privacy Analysis. PhD thesis, Dartmouth College Computer Science, Hanover, NH, August 2011. Available as Dartmouth Computer Science Technical Report TR2011-703. [Details]
• Phil Fazio, Keren Tan, Jihwang Yeo, and David Kotz. Short Paper: The NetSANI Framework for Analysis and Fine-tuning of Network Trace Sanitization. Proceedings of the ACM Conference on Wireless Network Security (WiSec), pages 5–10. ACM, June 2011. doi:10.1145/1998412.1998416. [Details]
• Phillip A. Fazio. Effects of network trace sampling methods on privacy and utility metrics. Technical Report number TR2011-697, Dartmouth College, Computer Science, Hanover, NH, June 2011. Senior Honors Thesis. [Details]
• Keren Tan, Guanhua Yan, Jihwang Yeo, and David Kotz. Privacy analysis of user association logs in a large-scale wireless LAN. Proceedings of the Annual Joint Conference of the IEEE Computer and Communications Societies (INFOCOM) mini-conference, pages 31–35. IEEE, April 2011. doi:10.1109/INFCOM.2011.5935168. [Details]
• Keren Tan, Guanhua Yan, Jihwang Yeo, and David Kotz. Privacy Analysis of User Association Logs in a Large-scale Wireless LAN. Technical Report number TR2011-679, Dartmouth Computer Science, January 2011. [Details]
• Keren Tan, Jihwang Yeo, Michael E. Locasto, and David Kotz. Catch, Clean, and Release: A Survey of Obstacles and Opportunities for Network Trace Sanitization. Privacy-Aware Knowledge Discovery: Novel Applications and New Techniques, chapter 5, pages 111–141. Edited by Francesco Bonchi and Elena Ferrari. Chapman and Hall/CRC Press, January 2011. ISBN13: 9781439803653. [Details]

2010:

• Keren Tan, Guanhua Yan, Jihwang Yeo, and David Kotz. A Correlation Attack Against User Mobility Privacy in a Large-scale WLAN network. Proceedings of the ACM MobiCom S3 workshop, pages 33–35. ACM, September 2010. doi:10.1145/1860039.1860050. [Details]

2009:

• Jihwang Yeo, Keren Tan, and David Kotz. User survey regarding the needs of network researchers in trace-anonymization tools. Technical Report number TR2009-658, Dartmouth Computer Science, Hanover, NH, November 2009. [Details]

[Kotz research]