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...

Increasing collection of individuals’ information has led to several security and privacy issues, such as identity theft and targeted marketing. These risks are further heightened in the mobile realm as data collection can occur continuously and ubiquitously. Most existing research considers threats to privacy and security as separate concerns, resulting in separate research streams. However, f...

We present a conceptual model of everyday privacy in ubiquitous computing environments, based on the works of Lessig and Adams. By everyday privacy, we mean the enduser’s ongoing exposure to and control over personal information collection. The model accounts for the influence of societal-scale forces, contextual factors, and subjective perception on end-user privacy. We identify notice and con...

Citizens’ privacy concerns have become a major barrier to their acceptance of e-government services, and the question of how to address these privacy issues effectively is increasingly important as government pushes service delivery online. Good protection of citizens’ privacy will contribute significantly to the success of e-government services. Therefore, it is highly desirable to take into a...