EyeSpot: Leveraging Gaze to Protect Private Text Content on Mobile Devices from Shoulder Surfing

Mohamed Khamis,Heinrich Hussmann,Martin Zürn,Malin Eiband

doi:10.3390/mti2030045

Mohamed Khamis, Heinrich Hussmann + Show 2 more

Open Access

https://doi.org/10.3390/mti2030045

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Abstract

As mobile devices allow access to an increasing amount of private data, using them in public can potentially leak sensitive information through shoulder surfing. This includes personal private data (e.g., in chat conversations) and business-related content (e.g., in emails). Leaking the former might infringe on users’ privacy, while leaking the latter is considered a breach of the EU’s General Data Protection Regulation as of May 2018. This creates a need for systems that protect sensitive data in public. We introduce EyeSpot, a technique that displays content through a spot that follows the user’s gaze while hiding the rest of the screen from an observer’s view through overlaid masks. We explore different configurations for EyeSpot in a user study in terms of users’ reading speed, text comprehension, and perceived workload. While our system is a proof of concept, we identify crystallized masks as a promising design candidate for further evaluation with regard to the security of the system in a shoulder surfing scenario.

Highlights

IntroductionUsers interact with their mobile devices in different contexts, ranging from private spaces, such as homes and offices, to public areas such as public transport, transit areas, and workplaces
Users interact with their mobile devices in different contexts, ranging from private spaces, such as homes and offices, to public areas such as public transport, transit areas, and workplaces.the convenience of being able to access sensitive data anywhere comes with the risk of exposing private information to bystanders through shoulder surfing
We introduce EyeSpot, a technique inspired by prior work on visual privacy protection [4,9] and privacy protection with eye tracking [8,10,11]

Summary

Introduction

Users interact with their mobile devices in different contexts, ranging from private spaces, such as homes and offices, to public areas such as public transport, transit areas, and workplaces. The convenience of being able to access sensitive data anywhere comes with the risk of exposing private information to bystanders through shoulder surfing. Revealed that interactions on mobile devices are often observed by bystanders which may leak sensitive private information about, for example, the user’s personal relationships, interests and plans [1]. These problems may potentially become more prominent with the increased popularity of larger screens of smartphones and tablets where the content that users are not interacting with is unnecessarily exposed. With growing tendency and expectations by employers and society to be always accessible, employees are more likely to engage in acts that compromise privacy, such as reading sensitive emails on the train

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