Privacy Risk Analysis fills a gap in the existing literature by providing an introduction to the basic notions, requirements, and main steps of conducting a privacy risk analysis. The deployment of new information technologies can lead to significant privacy risks and a privacy impact assessment should be conducted before designing a product or system that processes personal data. However, if existing privacy impact assessment frameworks and guidelines provide a good deal of details on organizational aspects (including budget allocation, resource allocation, stakeholder consultation, etc.), they are much vaguer on the technical part, in particular on the actual risk assessment task. For privacy impact assessments to keep up their promises and really play a decisive role in enhancing privacy protection, they should be more precise with regard to these technical aspects. This book is an excellent resource for anyone developing and/or currently running a risk analysis as it defines the notions of personal data, stakeholders, risk sources, feared events, and privacy harms all while showing how these notions are used in the risk analysis process. It includes a running smart grids example to illustrate all the notions discussed in the book.

The social benefit derived from Online Social Networks (OSNs) can lure users to reveal unprecedented volumes of personal data to an online audience that is much less trustworthy than their offline social circle. Even if a user hides his personal data from some users and shares with others, privacy settings of OSNs may be bypassed, thus leading to various privacy harms such as identity theft, stalking, or discrimination. Therefore, users need to be assisted in understanding the privacy risks of their OSN profiles as well as managing their privacy settings so as to keep such risks in check, while still deriving the benefits of social network participation. This book presents to its readers how privacy risk analysis concepts such as privacy harms and risk sources can be used to develop mechanisms for privacy scoring of user profiles and for supporting users in privacy settings management in the context of OSNs. Privacy scoring helps detect and minimize the risks due to the dissemination and use of personal data. The book also discusses many open problems in this area to encourage further research.