Carnegie Mellon University
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A Methodology for Information Flow Experiments

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posted on 1984-01-01, 00:00 authored by Michael Carl Tschantz, Amit Datta, Anupam DattaAnupam Datta, Jeannette M. Wing

Information flow analysis has largely ignored the setting where the analyst has neither control over nor a complete model of the analyzed system. We formalize such limited information flow analyses and study an instance of it: detecting the usage of data by websites. We prove that these problems are ones of causal inference. Leveraging this connection, we push beyond traditional information flow analysis to provide a systematic methodology based on experimental science and statistical analysis. Our methodology allows us to systematize prior works in the area viewing them as instances of a general approach. Our systematic study leads to practical advice for improving work on detecting data usage, a previously unformalized area. We illustrate these concepts with a series of experiments collecting data on the use of information by websites, which we statistically analyze

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1984-01-01

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