Tailoring Privacy-Aware Trustworthy Cooperating Smart Spaces for University Environments

Tailoring Privacy-Aware Trustworthy Cooperating Smart Spaces for University Environments

Nicolas Liampotis (National Technical University of Athens, Greece), Eliza Papadopoulou (Heriot-Watt University, UK), Nikos Kalatzis (National Technical University of Athens, Greece), Ioanna G. Roussaki (National Technical University of Athens, Greece), Pavlos Kosmides (National Technical University of Athens, Greece), Efstathios D. Sykas (National Technical University of Athens, Greece), Diana Bental (Heriot-Watt University, UK) and Nicholas Kenelm Taylor (Heriot-Watt University, UK)
DOI: 10.4018/978-1-4666-8732-5.ch016
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Abstract

The more information users disclose to pervasive systems or social media, the better quality and enhanced experience they enjoy for a wider variety of personalised services. However, the privacy concerns of individuals that use such systems have dramatically risen the last years, especially after several events of massive security breaches in various computing or communication systems that have reached the news. This chapter presents the approach being employed by the SOCIETIES project to protect the privacy of sensitive user data and ensure the trustworthiness of delivered services via social and pervasive computing systems. This framework has already been designed, implemented and evaluated via real user trials engaging wide and heterogeneous user populations. In addition to the respective requirements, architecture and features discussed herewith, this chapter elaborates on the user trial that has been conducted in university settings to validate this system focusing on the privacy and trust evaluation results obtained.
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Introduction

Latest advances in sensor technology and mobile devices have pushed forward the realisation and integration of pervasive computing (Hansmann et al., 2003; Minyi et al., 2014) in our everyday life. Sensors are embedded into objects, allowing them to obtain information from the physical world, while heterogeneous wireless networking technologies (e.g., WLAN, WiMAX, Bluetooth, LTE, UMTS, and GSM) enable sharing of information among them. Furthermore, with the advent of social media (Kaplan & Haenlein, 2010), vast amounts of personal information are being offered on a voluntary basis by the users themselves. The sensitivity of information that is disclosed, communicated and processed poses a threat to the privacy of the users, especially in cases where they are unable to fully understand and control the systems they are interacting with. These systems are responsible for providing appropriate mechanisms to ensure the protection of the privacy of their users.

It is a fact that absolute privacy can be achieved only if users do not disclose any personally identifying information. However, the pervasive computing and social networking paradigms depend on the availability of such information to provide value added services. Hence, there is a trade-off between the quality of user experience offered by these services and the preservation of user privacy. This chapter presents a privacy-enhancing framework that aims to assist users in maintaining a balance between protecting their privacy and enjoying the benefits of these technologies. This framework has been designed, implemented and evaluated within SOCIETIES, a European FP7 integrated project (http://www.ict-societies.eu), the vision of which is to transform traditional online social networks into pervasive communities.

A pervasive community is a group of two or more individuals who have agreed to share some of their resources, such as personal information, context data, services and devices with other members of that community. Towards the realisation of this paradigm, a set of community-centric concepts have been introduced (Doolin et al., 2012). On the one hand, a Cooperating Smart Space (CSS) represents a single participant (user or organisation) including their information and services within a distributed system of CSS nodes (user devices/cloud instances). On the other hand, a Community Interaction Space (CIS) represents and provides the interaction mechanisms for a pervasive community. CIS members interact via their own personal CSSs. The creation of a pervasive community or CIS is supported by discovering, connecting and organising relevant people and things from both physical and digital environments. This is accomplished by employing pervasive technologies, while leveraging social computing.

The usefulness of the CSS and CIS concepts has already been evaluated by three distinct user groups. One of these is the Student user group, which has been selected due to its ability to adapt to and accept new ideas and technologies. It is also the case that communication plays an important role in students’ lives as social networks have become an increasingly popular communication medium. Students are also less constrained in the ways they may use a CSS compared to other users, e.g. in the Enterprise or Disaster Management domain, where the CSS must serve a clear purpose. Students can therefore utilise a wide range of novel services enabled by a CSS ecosystem that integrates information from sensors in the environment, other users or communities, as well as, social media. For example, in university living scenarios, students with similar profiles, goals or interests can discover each other to discuss topics, share study notes and meet up when they are automatically discovered to be nearby.

Key Terms in this Chapter

Privacy: The right of individuals to protect their ability to selectively reveal information about themselves so as to negotiate social relationships most advantageous to them.

Privacy Policy: A legal document that discloses some or all of the ways a party gathers, uses, discloses and manages a customer’s data. The exact contents of a privacy policy will depend upon the applicable law and may need to address the requirements of multiple countries or jurisdictions.

Privacy Preference: Expresses a user’s wishes with regards to their privacy, i.e. the disclosure of their personal data and their processing after disclosure. A Privacy Preference can be dependent on the user’s context and/or the trustworthiness of the entity requesting access to user data.

Privacy Policy Negotiation: The process of making a mutual agreement between the privacy policy of a service provider and the privacy policy of a service consumer.

Indirect Trust: A trust relationship or a potential trust relationship built from recommendations (opinions) by a trusted third party or a chain of trusted parties (trust path).

Community Interaction Space (CIS): It’s a representation of a Pervasive Community and has one or more Cooperating Smart Spaces associated with it.

Trust Management: The activity of collecting, encoding, analysing and presenting evidence relating to competence, honesty, security or dependability with the purpose of making assessments and decisions regarding trust relationships.

Direct Trust: A trust relationship derived from the experiences of direct interactions between two parties.

Pervasive Community: A group of, two or more, individuals who have agreed to share some, but not necessarily all, of their pervasive resources, including personal information, context data, services, and devices, with other members of that group. A pervasive community, once constituted, forms a Community Interaction Space (CIS). There is a one-to-one mapping between pervasive communities and CISs.

Cooperating Smart Space (CSS): A CSS represents a single participant (user or organisation), and includes their information, and services within a distributed collection of CSS Nodes. It provides both a pervasive capability and a social networking capability in an integrated form. A CSS can be associated to zero or more Community Interaction Spaces (CIS), which are a representation of multi-participant community.

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