Reactive security

Templeman, Robert; Hoyle, Roberto; Crandall, David J.; Kapadia, Apu

doi:10.1145/2638728.2641708

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Privacy In Lifelogs1

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Cited by 7 publications

(1 citation statement)

References 27 publications

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“…This work focuses on the first one. Examples of approaches to protect the privacy include: physically marking objects that should not be captured [43], automated activation of personalized capturing policies in specific contexts [3,53,55], automatic or manual deletion of content upon detecting certain cues [31], and obfuscating parts of the photos [31,36,37].…”

Section: Privacy In Lifelogsmentioning

confidence: 99%

Impact of Privacy Protection Methods of Lifelogs on Remembered Memories

Elagroudy

Khamis

Mathis

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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Section: Privacy In Lifelogsmentioning

confidence: 99%

Impact of Privacy Protection Methods of Lifelogs on Remembered Memories

Elagroudy

Khamis

Mathis

et al. 2023

Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems

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PoliteCamera: Respecting Strangers’ Privacy in Mobile Photographing

2018

Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering

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Camera is a standard on-board sensor of modern mobile phones. It makes photo taking popular due to its convenience and high resolution. However, when users take a photo of a scenery, a building or a target person, a stranger may also be unintentionally captured in the photo. Such photos expose the location and activity of strangers, and hence may breach their privacy. In this paper, we propose a cooperative mobile photographing scheme called PoliteCamera to protect strangers' privacy. Through the cooperation between a photographer and a stranger, the stranger's face in a photo can be automatically blurred upon his request when the photo is taken. Since multiple strangers nearby the photographer might send out blurring requests but not all of them are in the photo, an adapted balanced convolutional neural network (ABCNN) is proposed to determine whether the requesting stranger is in the photo based on facial attributes. Evaluations demonstrate that the ABCNN can accurately predict facial attributes and PoliteCamera can provide accurate privacy protection for strangers.

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PrivacyCamera: Cooperative Privacy-Aware Photographing with Mobile Phones

Gao

2016

2016 13th Annual IEEE International Conference on Sensing, Communication, and Networking (SECON)

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Reactive security

Cited by 7 publications

References 27 publications

Impact of Privacy Protection Methods of Lifelogs on Remembered Memories

Impact of Privacy Protection Methods of Lifelogs on Remembered Memories

PoliteCamera: Respecting Strangers’ Privacy in Mobile Photographing

PrivacyCamera: Cooperative Privacy-Aware Photographing with Mobile Phones

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