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Title: Location privacy awareness on geo-social networks enhancing awareness with feedback solutions
Author: Alrayes, Fatma
ISNI:       0000 0004 7231 8843
Awarding Body: Cardiff University
Current Institution: Cardiff University
Date of Award: 2017
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Users of GeoSocial Networks (GeoSNs) share their personal location information with other users online. GeoSNs use spatiotemporal histories of users and other semantic information from their tags and comments to build location-based profiles and to offer personalised services and interaction experiences. However, such location-based profiles can potentially be used to extract private information about users, that they may not wish to disclose, and can thus pose a threat to their privacy. Users are generally unaware of the extent of data they are sharing and its potential implicit content. Studies have also shown that users are concerned about their location privacy and that current solutions offered by GeoSNs, namely privacy policies and privacy settings, do not effectively address their concerns. The focus of this thesis is on addressing the problem of location privacy on GeoSNs through enhancing users’ location privacy awareness of potential risks to allow them to make informed consent about their location disclosure. Therefore, this work firstly studies the link between location information disclosure and the risks to personal privacy and evaluates the level of user awareness and their attitude to privacy implications of sharing location information in GeoSNs. Factors contributing to the location privacy problem are identified, including those stemming from the nature of the data collection procedures and the modes of using the application by the users. Systematic user studies were carried out that showed the limitation in users’ awareness of the extent of the data and information they are disclosing. Thus, to enable location privacy awareness, a data-driven approach is undertaken to assessing the threat associated with the exposure of location-related personal information. Based on that, a privacy threat model is proposed that takes into account the types of shared data, its visibility by possible adversaries and the user’s awareness of the disclosed information. In addition, privacy feedback solutions are proposed to address the gaps in user awareness by revealing the level of risk to their privacy associated with exposing different types of location-related personal information. These solutions allow users to view their geo-profiles collected and inferred based on their location-sharing actions on GeoSNs and notify them about who of the other users can see their information. User-based experiments were used to evaluate the effectiveness of the proposed solutions using surveys, interviews, and prototypes along with realistic users’ data. Results demonstrate clearly the significance of the proposed solutions on enhancing user awareness. Employing the methods proposed in this thesis will thus enable users to effectively manage their privacy and make informed decisions about their location disclosure on GeoSNs.
Supervisor: Not available Sponsor: Not available
Qualification Name: Thesis (Ph.D.) Qualification Level: Doctoral
EThOS ID:  DOI: Not available