Short paper: the NetSANI framework for analysis and fine-tuning of network trace sanitization

Authors:
Phil Fazio;Keren Tan;Jihwang Yeo;David Kotz
Affiliations:
Dartmouth College, Hanover, NH, USA;Dartmouth College, Hanover, NH, USA;Dartmouth College, Hanover, NH, USA;Dartmouth College, Hanover, NH, USA
Venue:
Proceedings of the fourth ACM conference on Wireless network security
Year:
2011

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Abstract

Anonymization is critical prior to sharing wireless-network traces within the research community, to protect both personal and organizational sensitive information from disclosure. One difficulty in anonymization, or more generally, sanitization, is that users lack information about the quality of a sanitization result, such as how much privacy risk a sanitized trace may expose, and how much research utility the sanitized trace may retain. We propose a framework, NetSANI, that allows users to analyze and control the privacy/utility tradeoff in network sanitization. NetSANI can accommodate most of the currently available privacy and utility metrics for network trace sanitization. This framework provides a set of APIs for analyzing the privacy/utility tradeoff by comparing the changes in privacy and utility levels of a trace for a sanitization operation. We demonstrate the framework with an quantitative evaluation on wireless-network traces.