Smart privacy-preserving screen based on multiple sensor fusion

Lian, Shiguo; Hu, Wei; Song, Xianfeng; Liu, Zhaoxiang

doi:10.1109/tce.2013.6490252

Cited by 18 publications

(14 citation statements)

References 16 publications

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“…In contrast to the manifold work which was published to protect the authentication process, general visual privacy concepts have not been in focus of research and related work is quite sparse. Besides the use of physical privacy foils which limit the angle of view [34], adaptive sensor-based approaches (e.g., [2,7,28,54]) and static software-based ap-proaches (e.g., [14,41,47]) have been discussed. Sensorbased approaches are usually checking the user's surrounding and indicate bystanders.…”

Section: Related Workmentioning

confidence: 99%

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Understanding Shoulder Surfing in the Wild

Eiband

Khamis

Zezschwitz

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

136

140

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Research has brought forth a variety of authentication systems to mitigate observation attacks. However, there is little work about shoulder surfing situations in the real world. We present the results of a user survey (N=174) in which we investigate actual stories about shoulder surfing on mobile devices from both users and observers. Our analysis indicates that shoulder surfing mainly occurs in an opportunistic, nonmalicious way. It usually does not have serious consequences, but evokes negative feelings for both parties, resulting in a variety of coping strategies. Observed data was personal in most cases and ranged from information about interests and hobbies to login data and intimate details about third persons and relationships. Thus, our work contributes evidence for shoulder surfing in the real world and informs implications for the design of privacy protection mechanisms.

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Section: Related Workmentioning

confidence: 99%

“…Sensorbased approaches are usually checking the user's surrounding and indicate bystanders. If potential observers are detected, the user is either informed (e.g., [2,7]) or the user interface is adapted (e.g., [7,28,54]). Such adaptions imply reducing the screen's lightness or selectively hiding information [41].…”

Section: Related Workmentioning

confidence: 99%

Understanding Shoulder Surfing in the Wild

Eiband

Khamis

Zezschwitz

et al. 2017

Proceedings of the 2017 CHI Conference on Human Factors in Computing Systems

136

140

View full text Add to dashboard Cite

show abstract

“…Apart from authentication, eye tracking has also been used for visual privacy protection. For example, Lian et al detected eyes in video frames to determine whether anyone is shoulder surfing the user; if eyes are detected, the brightness of the screen is adapted accordingly [33]. Brudy et al used a Kinect to estimate the gaze direction of passers-by in front of a large public display and visualized it to users of the display to make them aware of shoulder surfers [13].…”

Section: Privacy Protection Using Eye Trackingmentioning

confidence: 99%

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

Khamis

Eiband

Zürn

et al. 2018

MTI

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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.

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“…Brudy et al explored how proximity information can be leveraged to detect and provide awareness of shoulder surfing moments through visual cues and to respond via a range of software-based means to protect information on large public displays [2]. Lian et al proposed a privacy-preserving screen system that automatically adjusts screen brightness based on screen peeping detection, user distance and environmental brightness [7].…”

Section: Related Workmentioning

confidence: 99%

Somebody Is Peeking!

Zhou

Ferreira

Alves

et al. 2015

Proceedings of the 33rd Annual ACM Conference Extended Abstracts on Human Factors in Computing Systems

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As smartphones and tablets are now widespread, accessing or even sharing sensitive content in public areas has become commonplace. This applies to both personal contexts (e.g. checking banking information in a coffee shop) and professional contexts (e.g. sharing patient information in a hospital ward). It is important to explore ways to support visual privacy that are appropriate for mobile device use in public settings and in dynamic workflows. In this paper we present the design, prototype implementation, and ongoing evaluation of a range of privacy notifications and privacy control mechanisms for tablets. Preliminary results show that: 1) spatial information such as distance and orientation can be used to mediate privacy management for tablet interfaces. 2) Privacy notifications and control mechanisms should be designed to complement our existing physical awareness and protection mechanisms. 3) Selecting a specific design is highly context-dependent.

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Smart privacy-preserving screen based on multiple sensor fusion

Cited by 18 publications

References 16 publications

Understanding Shoulder Surfing in the Wild

Understanding Shoulder Surfing in the Wild

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

Somebody Is Peeking!

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