Preface
"Data can be either useful or perfectly anonymous but never both" (Ohm, 2010)
Online behavioral data is a valuable source of insights for researchers. However, data collected passively via tracking meters contains Personal Identifiable Information (Pll). With the GDPR into force, the value of online behavioral data is constrained by the risk of disclosing Pll. We present a machine-learning solution that significantly reduces the risk of revealing Pll when sharing browsing data.
Introduction
When asked about a certain experience, we try to describe it to the best of our ability. However, our memories may be affected by our...