Tools for Achieving Usable Ex Post Transparency: A Survey <s> 4) ONLINE SOCIAL NETWORK <s> The rapid adoption of location tracking and mobile social networking technologies raises significant privacy challenges. Today our understanding of people's location sharing privacy preferences remains very limited, including how these preferences are impacted by the type of location tracking device or the nature of the locations visited. To address this gap, we deployed Locaccino, a mobile location sharing system, in a four week long field study, where we examined the behavior of study participants (n=28) who shared their location with their acquaintances (n=373.) Our results show that users appear more comfortable sharing their presence at locations visited by a large and diverse set of people. Our study also indicates that people who visit a wider number of places tend to also be the subject of a greater number of requests for their locations. Over time these same people tend to also evolve more sophisticated privacy preferences, reflected by an increase in time- and location-based restrictions. We conclude by discussing the implications our findings. <s> BIB001 </s> Tools for Achieving Usable Ex Post Transparency: A Survey <s> 4) ONLINE SOCIAL NETWORK <s> One of the main security concerns related to the cloud hosting and virtualization, is the lack of Trust in the infrastructure. This lack of trust is due to the absence of transparency concerning the data handling and storage conditions. There are no concrete technical guarantees that can convince a potential cloud customer that he is fully controlling his data. In this paper we propose a security service (called SPACE) in the cloud that provides all the tools to data owner to impose his privacy preferences during the virtualization phase. SPACE is based on the sticky policy technology and offers access and usage control functionalities to the data anywhere in the cloud. In addition to the main security features offered by SPACE, new visualization and control functionalities are proposed to make the user fully aware on the storage condition of his private information. <s> BIB002 </s> Tools for Achieving Usable Ex Post Transparency: A Survey <s> 4) ONLINE SOCIAL NETWORK <s> Personal and contextual information are increasingly shared via mobile social networks. Users' locations, activities and their co-presence can be shared easily with online "friends", as their smartphones already access such information from embedded sensors and storage. Yet, people usually exhibit selective sharing behavior depending on contextual attributes, thus showing that privacy, utility, and usability are paramount to the success of such online services. In this paper, we present SPISM, a novel information-sharing system that decides (semi-)automatically whether to share information with others, whenever they request it, and at what granularity. Based on active machine learning and context, SPISM adapts to each user's behavior and it predicts the level of detail for each sharing decision, without revealing any personal information to a third-party. Based on a personalized survey about information sharing involving 70 participants, our results provide insight into the most influential features behind a sharing decision. Moreover, we investigate the reasons for the users' decisions and their confidence in them. We show that SPISM outperforms other kinds of global and individual policies, by achieving up to 90% of correct decisions. <s> BIB003 </s> Tools for Achieving Usable Ex Post Transparency: A Survey <s> 4) ONLINE SOCIAL NETWORK <s> Information sharing on the Internet has become a streamlined process through services such as e-mail, blogs and recently also Online Social Networks (OSNs). The speed of posting information in one central place and the convenience of this information reaching a vast audience at the same time is a great advantage of this style of communication, but at the same time also a danger. The aim of this article is thus to introduce a prototype software model that can analyse not only the Personally Identifiable Information (PII) that users share on OSNs, but with whom they share this. Such analysis will give users a good indication of how their private information is shared based on different settings within their OSN profiles. To successfully develop such a model, familiarity with the concepts of information sharing and PII is firstly investigated. Identifying information leakage within one of the most popular OSNs follows. In combination with our programming knowledge, a prototype model is introduced and an overview of preliminary results is given. Due to the generic nature of the model, we are able to visually introduce and explain the process of information deduction -- an aspect of information sharing often overlooked due to its invisible nature. After analysing the information gathered from our model, we conclude that the immense popularity of Facebook on both a global and local scale contribute to its success, but at the same time make its users more prone to leak information and subsequently be the potential targets of cyber criminals. The ease, anonymity and borderless nature of the Internet in combination with the poor default security settings of our investigated OSN all contribute to the lucrative industry of cyber crime. Proper user awareness is crucial to preventing the leaking of any information in an online environment, but for many users this still equates to (a) PII in the sky. <s> BIB004
Online social networks (OSNs) signify a special kind of online service dedicated to managing personal and group relationships in the context of specific interest groups. Social networks epitomise the large scale amalgamation and distribution of personal data to either subgroups of the network or the entire public. OSNs such as Facebook and Google+ allow for implementing customised services tailored for subgroups of these networks. Such add-ons can be as broad or narrow as is required to satisfy the demands of the respective interest group. OSN add-ons can leverage vast numbers of actors and tap into social structures that represent specific categories of socio-cultural backgrounds. The TETs presented by Bilogrevic et al. BIB003 , Louw et al. BIB004 , Toch et al. BIB001 , and Trabelsi et al. BIB002 specifically rely on the group structures and inter-person relationships reflected by OSNs. Kolter et al.  suggest publishing insight gathered about the behaviour of a particular service provider on a wiki-based collaborative platform. Other users are encouraged to comment on and rate these records in order to allow for community-driven statements about the trustworthiness of respective service providers. Table 3 provides a comprehensive list of the hosting platforms of the reviewed ex post TETs keyed by operating system and run-time environment.