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Full-Text Articles in Physical Sciences and Mathematics
Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau
Obfuscation At-Source: Privacy In Context-Aware Mobile Crowd-Sourcing, Thivya Kandappu, Archan Misra, Shih-Fen Cheng, Randy Tandriansyah, Hoong Chuin Lau
Research Collection School Of Computing and Information Systems
By effectively reaching out to and engaging larger population of mobile users, mobile crowd-sourcing has become a strategy to perform large amount of urban tasks. The recent empirical studies have shown that compared to the pull-based approach, which expects the users to browse through the list of tasks to perform, the push-based approach that actively recommends tasks can greatly improve the overall system performance. As the efficiency of the push-based approach is achieved by incorporating worker's mobility traces, privacy is naturally a concern. In this paper, we propose a novel, 2-stage and user-controlled obfuscation technique that provides a trade off-amenable …
Secure Server-Aided Top-K Monitoring, Yujue Wang, Hwee Hwa Pang, Yanjiang Yang, Xuhua Ding
Secure Server-Aided Top-K Monitoring, Yujue Wang, Hwee Hwa Pang, Yanjiang Yang, Xuhua Ding
Research Collection School Of Computing and Information Systems
In a data streaming model, a data owner releases records or documents to a set of users with matching interests, in such a way that the match in interest can be calculated from the correlation between each pair of document and user query. For scalability and availability reasons, this calculation is delegated to third-party servers, which gives rise to the need to protect the integrity and privacy of the documents and user queries. In this paper, we propose a server-aided data stream monitoring scheme (DSM) to address the aforementioned integrity and privacy challenges, so that the users are able to …
You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan
You Are Being Watched: Bystanders' Perspective On The Use Of Camera Devices In Public Spaces, Samarth Singhal, Carman Neustaedter, Thecla Schiphorst, Anthony Tang, Abhisekh Patra, Rui Pan
Research Collection School Of Computing and Information Systems
We are observing an increase in the use of smartphones and wearable devices in public places for streaming and recording video. Yet the use of cameras in these devices can infringe upon the privacy of the people in the surrounding environment by inadvertently capturing them. This paper presents findings from an in-situ exploratory study that investigates bystanders' reactions and feelings towards streaming and recording videos with smartphones and wearable glasses in public spaces. We use the interview results to guide an exploration of design directions for mobile video.
Uncovering Embarrassing Moments In In-Situ Exposure Of Incoming Mobile Messages, Chulhong Min, Saumay Pushp, Seungchul Lee, Inseok Hwang, Youngki Lee, Seungwoo Kang, Junehwa Song
Uncovering Embarrassing Moments In In-Situ Exposure Of Incoming Mobile Messages, Chulhong Min, Saumay Pushp, Seungchul Lee, Inseok Hwang, Youngki Lee, Seungwoo Kang, Junehwa Song
Research Collection School Of Computing and Information Systems
Mobile instant messengers serve as major interaction media for everyday chats. Contrary to the belief that a message is seen only by a designated receiver, it can be accidentally exposed to someone nearby and could result in embarrassing moments, for example, when the receiver is viewing pictures together with his friend upon the message arrival. To understand the significance of the problem and core factors that cause such embarrassments, we collected 961 in-situ responses from 14 participants upon the actual message arrival and analyzed them from the perspective of the receiver's situation. The results showed that 29% of message arrivals …
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Exposing And Mitigating Privacy Loss In Crowdsourced Survey Platforms, Thivya Kandappu, Vijay Sivaraman, Arik Friedman, Roksana Borell
Research Collection School Of Computing and Information Systems
Crowdsourcing platforms such as Amazon Mechanical Turk and Google Consumer Surveys can profile users based on their inputs to online surveys. In this work we first demonstrate how easily user privacy can be compromised by collating information from multiple surveys. We then propose, develop, and evaluate a crowdsourcing survey platform called Loki that allows users to control their privacy loss via atsource obfuscation.
Server-Assisted Context-Dependent Pervasive Wellness Monitoring, Archan Misra, Ben Falchuk, Shoshana Loeb
Server-Assisted Context-Dependent Pervasive Wellness Monitoring, Archan Misra, Ben Falchuk, Shoshana Loeb
Research Collection School Of Computing and Information Systems
Recent research on remote health monitoring solutions has focused largely on developing context-dependent, streamprocessing capabilities on a personal mobile hub (typically, a cellphone) for energy-efficient transmission of data collected from a set of body-worn medical sensors. In this paper, we argue that commercial deployment of such pervasive wellness monitoring will require the extension of such ‘context dependency’ to the process of data collection (from the sensors to the mobile device) as well. In particular, the utilization of an individuals non-medical activity context, by the cellphone, in coordination with a backend server, is posited to be the key to supporting important …