Privacy is one of the most essential topics to be investigated when assessing user acceptance of new applications and services enabling disclosure of personal information. Mobility increases the demand on taking privacy into consideration when designing and developing these kinds of systems. This chapter presents a privacy management model, which facilitates evaluation of privacy aspects of com...

We consider the problem of fitting a linear model to data held by individuals who are concerned about their privacy. Incentivizing most players to report their data to the analyst truthfully constrains our design to mechanisms that provide a privacy guarantee to the participants; we use differentially privacy to model individuals’ privacy losses. This immediately poses a problem, as differentia...

Safeguarding location privacy is becoming a critical issue in locationbased services and location-aware computing generally. Two drawbacks of many previous models of location privacy are: 1) the models only consider a person’s location privacy protection, but not the invasion of location privacy by external agents; and 2) the models are static and do not consider the spatiotemporal aspects of m...

In this paper, we propose a privacy model that offers trajectory privacy to the requesters of Location-Based Services (LBSs), by utilizing an underlying network of user movement. The privacy model has been implemented as a framework that (i) reconstructs the user movement from a series of independent location updates, (ii) identifies routes where user privacy is at risk, and (iii) anonymizes on...

Photo privacy is a very important problem in the digital age where photos are commonly shared on social networking sites and mobile devices. The main challenge in photo privacy detection is how to generate discriminant features to accurately detect privacy at risk photos. Existing photo privacy detection works, which rely on low-level vision features, are non-informative to the users regarding ...

We present a unified model of everyday privacy in ubiquitous computing environments, designed to aid system designers and administrators in conceptualizing the end-user privacy experience. The model accounts for the influence of societal-scale forces, contextual factors, and subjective perception on end-user privacy. We identify notice and consent as the fair information practices of greatest e...

To date, the issues of privacy and security remain poorly addressed within robotics at large. In this work, we provide a foundation for analyzing the privacy of swarms of heterogeneous robots. Our premise is that information pertaining to individual robot types must be kept private in order to preserve the security and resilience of the swarm system at large. A main contribution is the developm...

With the development of cloud computing, more and more service providers deploy multitenant applications to the cloud. Multi-tenant data is stored by non-fully trusted SaaS service providers, and the protection of data privacy attracts more attention. This paper proposes a privacy protection strategy customization framework. This framework considers the privacy protection needs, SaaS applicatio...

We present a unified model of everyday privacy in ubiquitous computing environments, designed to aid system designers and administrators in conceptualizing the end-user privacy experience. The model accounts for the influence of societal-scale forces, contextual factors, and subjective perception on end-user privacy. We identify notice and consent as the fair information practices of greatest e...