Context-driven prevention of unintended identity disclosure

Workshop on Security in Ubiquitous Computing, 4th …, 2002

2011

Abstract Context-awareness enables applications to better streamline and personalize their service according to the current situation of the user. However, the user's information used by context-aware applications, such as the user's current location, is inherently private and sensitive. Using this information without proper control by the user can lead to privacy risks and might harm the trust users have in the context-aware application.

2011 IEEE Fifth International Conference on Semantic Computing, 2011

Recent years have seen a confluence of two major trends-the increase of mobile devices such as smart phones as the primary access point to networked information and the rise of social media platforms that connect people. Their convergence supports the emergence of a new class of context-aware geosocial networking applications. While existing systems focus mostly on location, our work centers on models for representing and reasoning about a more inclusive and higher-level notion of context, including the user's location and surroundings, the presence of other people and devices, and the inferred activities in which they are engaged. A key element of our work is the use of collaborative information sharing where devices share and integrate knowledge about their context. This introduces the need for privacy and security mechanisms. We present a framework to provide users with appropriate levels of privacy to protect the personal information their mobile devices are collecting, including the inferences that can be drawn from the information. We use Semantic Web technologies to specify high-level, declarative policies that describe user information sharing preferences. We have built a prototype system that aggregates information from a variety of sensors on the phone, online sources, and sources internal to the campus intranet, and infers the dynamic user context. We show how our policy framework can be effectively used to devise better privacy control mechanisms to control information flow between users in such dynamic mobile systems.

Third IEEE International Conference on Pervasive Computing and Communications Workshops, 2005

Privacy is widely recognised as a significant obstacle inhibiting the adoption of context-aware applications. In order to remove this obstacle, advances are required in many areas of context-awareness research. In this paper, we address the incorporation of privacy support into context models. In particular, we present extensions to our context modelling approach that address the challenges of assigning ownership to context information and enabling users to express privacy preferences for their own information.

2012

In ubiquitous systems control of privacy settings will be increasingly difficult due to the pervasive nature of sensing and communication capabilities. We identify challenges for privacy decisions in ubiquitous systems and propose a system for in situ privacy decision support. When context changes occur, the system adapts a user's privacy preferences to the new situation. As a consequence, recommendations can be offered to the user or sharing behavior can be automatically adjusted to help the user maintain a desired level of privacy. The system learns from user interaction and behavior to improve decision accuracy. In this paper, we outline the main components of our system and illustrate its operation with an ambient assisted living use case.

2011

Context-aware systems aim to deliver a richer user experience by taking into account the current user context (location, time, activity, etc.), possibly captured without his intervention. For example, cellphones are now able to continuously update the user's location while, at the same time, users execute an increasing amount of activities online, where their actions may be easily captured (e.g., login in a web application) without user consent. The potential advantages of these applications is huge, but we must not forget the important privacy issues that it creates. Particularly in distributed context-aware systems where the information that is captured may be sent to a distant server, people feel uncomfortable about exposing highly personal data, such as their location or current activity. This paper examines the current privacy management techniques and identifies four main groups: Privacy Policies, Data Perturbation, Anonymization and Lookup Notification. Each of these groups is analyzed highlighting the advantages and disadvantages of their application to Distributed Context-Aware Systems.

Ubicomp 2002 Workshop on Socially- …, 2002

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 consent as the fair information practices of greatest everyday utility to users, as they gradually engender the user's conceptual model of ubicomp privacy. Navigating the regular deluge of personal information collection events in ubicomp requires that notice be minimally intrusive and consent be implicitly granted by a persistent, situation-specific set of user preferences. We extend our model into an interactional metaphor called faces, designed to mitigate the complexity of privacy for the end-user. Users vary the face they wear depending on the recipient and/or situation, where a face is a meaningful encapsulation of privacy preferences.

2000

2014 47th Hawaii International Conference on System Sciences, 2014

Evidences collected from smartphones users show a growing desire of personalization offered by services for mobile devices. However, the need to accurately identify users' contexts has important implications for user's privacy and it increases the amount of trust, which users are requested to have in the service providers. In this paper, we introduce a model that describes the role of personalization and control in users' assessment of cost and benefits associated to the disclosure of private information. We present an instantiation of such model, a context-aware application for smartphones based on the Android operating system, in which users' private information are protected. Focus group interviews were conducted to examine users' privacy concerns before and after having used our application. Obtained results confirm the utility of our artifact and provide support to our theoretical model, which extends previous literature on privacy calculus and user's acceptance of contextaware technology.

2003

The goal of everyday privacy is to make it easy for endusers to share information with the right people at the right level of detail in ubiquitous computing environments. In this paper, we describe a conceptual model we have developed for everyday privacy, consisting of control over and feedback about disclosure. We also describe a prototype we have created for helping end-users manage their personal privacy, an evaluation of that prototype, and a revised prototype based on feedback from the ...