It wasn't me! Plausible Deniability in Web Search
This addresses privacy concerns for internet users by providing practical defenses against search engine tracking, though it appears incremental as it builds on existing detection and obfuscation methods.
The paper tackles the problem of protecting user privacy against search engine personalization by developing tools to detect, assess, and defend threats to plausible deniability, showing that threats are detectable across all tested topics and that a defense using proxy topics is more effective in experiments.
Our ability to control the flow of sensitive personal information to online systems is key to trust in personal privacy on the internet. We ask how to detect, assess and defend user privacy in the face of search engine personalisation? We develop practical and scalable tools allowing a user to detect, assess and defend against threats to plausible deniability. We show that threats to plausible deniability of interest are readily detectable for all topics tested in an extensive testing program. We show this remains the case when attempting to disrupt search engine learning through noise query injection and click obfuscation are used. We use our model we design a defence technique exploiting uninteresting, proxy topics and show that it provides amore effective defence of plausible deniability in our experiments.