# Plausible Deniability in Web Search -- From Detection to Assessment

## TL;DR

This paper introduces \\PDE{}, a scalable tool to detect and assess threats to users' plausible deniability in web search, revealing vulnerabilities especially in sensitive topics and proposing a defense method using proxy topics.

## Contribution

The paper presents a practical tool for detecting threats to plausible deniability in web search and evaluates defense strategies against search engine learning attacks.

## Key findings

- Threats to deniability are easily detectable across tested topics.
- Sensitive topics like health and sexual preferences are particularly vulnerable.
- Proxy topics can effectively defend plausible deniability.

## Abstract

We ask how to defend user ability to plausibly deny their interest in topics deemed sensitive in the face of search engine learning. We develop a practical and scalable tool called \PDE{} allowing a user to detect and assess 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. Of particular concern is observation of threats to deniability of interest in topics related to health and sexual preferences. We show this remains the case when attempting to disrupt search engine learning through noise query injection and click obfuscation. We design a defence technique exploiting uninteresting, proxy topics and show that it provides a more effective defence of plausible deniability in our experiments.