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.

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.

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.