"Do You Know You Are Tracked by Photos That You Didn't Take": Location-Aware Multi-Party Image Privacy Protection

TL;DR

This paper introduces LAMP, a system that enhances image privacy by detecting individuals in photos and replacing their faces based on location-sensitive privacy policies, addressing background exposure and route inference issues.

Contribution

The paper presents a novel location-aware multi-party image access control model and a system that automatically detects and protects individuals in shared images, including background persons.

Findings

Prototype implementation demonstrates real-world applicability.

System effectively detects and replaces faces based on privacy policies.

Addresses background exposure and travel route inference risks.

Abstract

Most existing image privacy protection works focus mainly on the privacy of photo owners and their friends, but lack the consideration of other people who are in the background of the photos and the related location privacy issues. In fact, when a person is in the background of someone else's photos, he/she may be unintentionally exposed to the public when the photo owner shares the photo online. Not only a single visited place could be exposed, attackers may also be able to piece together a person's travel route from images. In this paper, we propose a novel image privacy protection system, called LAMP, which aims to light up the location awareness for people during online image sharing. The LAMP system is based on a newly designed location-aware multi-party image access control model. The LAMP system will automatically detect the user's occurrences on photos regardless the user is the photo owner or not. Once a user is identified and the location of the photo is deemed sensitive according to the user's privacy policy, the LAMP system will intelligently replace the user's face. A prototype of the system was implemented and evaluated to demonstrate its applicability in the real world.