PrivacEye: Privacy-Preserving Head-Mounted Eye Tracking Using Egocentric Scene Image and Eye Movement Features

Eyewear devices, such as augmented reality displays, increasingly integrate eye tracking but the first-person camera required to map a user's gaze to the visual scene can pose a significant threat to user and bystander privacy. We present PrivacEye, a method to detect privacy-sensitive everyday situations and automatically enable and disable the eye tracker's first-person camera using a mechanical shutter. To close the shutter in privacy-sensitive situations, the method uses a deep representation of the first-person video combined with rich features that encode users' eye movements. To open the shutter without visual input, PrivacEye detects changes in users' eye movements alone to gauge changes in the "privacy level" of the current situation. We evaluate our method on a first-person video dataset recorded in daily life situations of 17 participants, annotated by themselves for privacy sensitivity, and show that our method is effective in preserving privacy in this challenging setting.Comment: 10 pages, 6 figures, supplementary materia

一人称ライフログ映像からの顔検出に基づいた社会活動計測

指導教員：角　康

Interdisciplinary perspectives on privacy awareness in lifelogging technology development

Population aging resulting from demographic changes requires some challenging decisions and necessary steps to be taken by different stakeholders to manage current and future demand for assistance and support. The consequences of population aging can be mitigated to some extent by assisting technologies that can support the autonomous living of older individuals and persons in need of care in their private environments as long as possible. A variety of technical solutions are already available on the market, but privacy protection is a serious, often neglected, issue when using such (assisting) technology. Thus, privacy needs to be thoroughly taken under consideration in this context. In a three-year project PAAL (‘Privacy-Aware and Acceptable Lifelogging Services for Older and Frail People’), researchers from different disciplines, such as law, rehabilitation, human-computer interaction, and computer science, investigated the phenomenon of privacy when using assistive lifelogging technologies. In concrete terms, the concept of Privacy by Design was realized using two exemplary lifelogging applications in private and professional environments. A user-centered empirical approach was applied to the lifelogging technologies, investigating the perceptions and attitudes of (older) users with different health-related and biographical profiles. The knowledge gained through the interdisciplinary collaboration can improve the implementation and optimization of assistive applications. In this paper, partners of the PAAL project present insights gained from their cross-national, interdisciplinary work regarding privacy-aware and acceptable lifelogging technologies.Open Access funding enabled and organized by Projekt DEAL. This work is part of the PAAL-project (“Privacy-Aware and Acceptable Lifelogging services for older and frail people”). The support of the Joint Programme Initiative “More Years, Better Lives” (award number: PAAL_JTC2017), the German Federal Ministry of Education and Research (grant no: 16SV7955), the Swedish Research Council for Health, Working Life, and Welfare (grant no: 2017–02302), the Spanish Agencia Estatal de Investigacion (PCIN-2017-114), the Italian Ministero dell’Istruzione dell’Universitá e della Ricerca, (CUP: I36G17000380001), and the Canadian Institutes of Health Research is gratefully acknowledged

A privacy-aware and secure system for human memory augmentation

The ubiquity of digital sensors embedded in today's mobile and wearable devices (e.g., smartphones, wearable cameras, wristbands) has made technology more intertwined with our life. Among many other things, this allows us to seamlessly log our daily experiences in increasing numbers and quality, a process known as ``lifelogging''. This practice produces a great amount of pictures and videos that can potentially improve human memory. Consider how a single photograph can bring back distant childhood memories, or how a song can help us reminisce about our last vacation. Such a vision of a ``memory augmentation system'' can offer considerable benefits, but it also raises new security and privacy challenges. Maybe obviously, a system that captures everywhere we go, and everything we say, see, and do, is greatly increasing the danger to our privacy. Any data breach of such a memory repository, whether accidental or malicious, could negatively impact both our professional and private reputation. In addition, the threat of memory manipulation might be the most worrisome aspect of a memory augmentation system: if an attacker is able to remove, add, or change our captured information, the resulting data may implant memories in our heads that never took place, or, in turn, accelerate the loss of other memories. Starting from such key challenges, this thesis investigates how to design secure memory augmentation systems. In the course of this research, we develop tools and prototypes that can be applied by researchers and system engineers to develop pervasive applications that help users capture and later recall episodic memories in a secure fashion. We build trusted sensors and protocols to securely capture and store experience data, and secure software for the secure and privacy-aware exchange of experience data with others. We explore the suitability of various access control models to put users in control of the plethora of data that the system captures on their behalf. We also explore the possibility of using in situ physical gestures to control different aspects regarding the capturing and sharing of experience data. Ultimately, this thesis contributes to the design and development of secure systems for memory augmentation