Quantitative Information Flow (QIF)

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Quantitative Information Flow (QIF) is the area of knowledge concerned with measuring and controlling the amount of information that flows from a source (who knows the information) to a target (who does not yet know it).

In some cases the flow of information is intended to be facilitated (e.g., when available training data provides useful information to a machine learning algorithm), whereas in other cases it should be prevented (e.g., when protecting an internet baking user’s account information). Usually, however, the aims are a careful mix of the two: to let information flow to those who need to know it, but to keep it from those who must not have it. The QIF framework allows for the precise quantification of information flow in computational systems, including measuring leaks in computational programs (e.g., election systems), in communication protocols (e.g., TOR), in the disclosure of statistical information (e.g., government census or medical research), among many others.