FacePET: Enhancing Bystanders\u27 Facial Privacy with Smart Wearables/Internet of Things

Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the bystanders’ trust in these systems to protect his/her facial privacy. To address these limitations, we propose FacePET (Facial Privacy Enhancing Technology), a wearable system worn by bystanders and designed to enhance facial privacy. We present the design, implementation, and evaluation of the FacePET and discuss some open research issues

A User Study of a Wearable System to Enhance Bystanders’ Facial Privacy

The privacy of users and information are becoming increasingly important with the growth and pervasive use of mobile devices such as wearables, mobile phones, drones, and Internet of Things (IoT) devices. Today many of these mobile devices are equipped with cameras which enable users to take pictures and record videos anytime they need to do so. In many such cases, bystanders’ privacy is not a concern, and as a result, audio and video of bystanders are often captured without their consent. We present results from a user study in which 21 participants were asked to use a wearable system called FacePET developed to enhance bystanders’ facial privacy by providing a way for bystanders to protect their own privacy rather than relying on external systems for protection. While past works in the literature focused on privacy perceptions of bystanders when photographed in public/shared spaces, there has not been research with a focus on user perceptions of bystander-based wearable devices to enhance privacy. Thus, in this work, we focus on user perceptions of the FacePET device and/or similar wearables to enhance bystanders’ facial privacy. In our study, we found that 16 participants would use FacePET or similar devices to enhance their facial privacy, and 17 participants agreed that if smart glasses had features to conceal users’ identities, it would allow them to become more popular

FacePET: Enhancing bystanders’ facial privacy with smart wearables/internet of things

© 2018 by the authors. Licensee MDPI, Basel, Switzerland. Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the bystanders’ trust in these systems to protect his/her facial privacy. To address these limitations, we propose FacePET (Facial Privacy Enhancing Technology), a wearable system worn by bystanders and designed to enhance facial privacy. We present the design, implementation, and evaluation of the FacePET and discuss some open research issues

FacePET: Enhancing Bystanders’ Facial Privacy with Smart Wearables/Internet of Things

Given the availability of cameras in mobile phones, drones and Internet-connected devices, facial privacy has become an area of major interest in the last few years, especially when photos are captured and can be used to identify bystanders’ faces who may have not given consent for these photos to be taken and be identified. Some solutions to protect facial privacy in photos currently exist. However, many of these solutions do not give a choice to bystanders because they rely on algorithms that de-identify photos or protocols to deactivate devices and systems not controlled by bystanders, thereby being dependent on the bystanders’ trust in these systems to protect his/her facial privacy. To address these limitations, we propose FacePET (Facial Privacy Enhancing Technology), a wearable system worn by bystanders and designed to enhance facial privacy. We present the design, implementation, and evaluation of the FacePET and discuss some open research issues