The enormous success and diffusion that online social networks (OSNs) are encountering nowadays is vastly apparent. Users' social interactions now occur using online social media as communication channels; personal information and activities are easily exchanged both for recreational and business purposes in order to obtain social or economic advantages. In this scenario, OSNs are considered critical applications with respect to the security of users and their resources, for their characteristics alone: the large amount of personal information they manage, big economic upturn connected to their commercial use, strict interconnection among users and resources characterizing them, as well as user attitude to easily share private data and activities with strangers. In this book, we discuss three main research topics connected to security in online social networks: (i) trust management, because trust can be intended as a measure of the perception of security (in terms of risks/benefits) that users in an OSN have with respect to other (unknown/little-known) parties; (ii) controlled information sharing, because in OSNs, where personal information is not only connected to user profiles, but spans across users' social activities and interactions, users must be provided with the possibility to directly control information flows; and (iii) identity management, because OSNs are subjected more and more to malicious attacks that, with respect to traditional ones, have the advantage of being more effective by leveraging the social network as a new medium for reaching victims. For each of these research topics, in this book we provide both theoretical concepts as well as an overview of the main solutions that commercial/non-commercial actors have proposed over the years. We also discuss some of the most promising research directions in these fields.

Social media greatly enables people to participate in online activities and shatters the barrier for online users to create and share information at any place at any time. However, the explosion of user-generated content poses novel challenges for online users to find relevant information, or, in other words, exacerbates the information overload problem. On the other hand, the quality of user-generated content can vary dramatically from excellence to abuse or spam, resulting in a problem of information credibility. The study and understanding of trust can lead to an effective approach to addressing both information overload and credibility problems. Trust refers to a relationship between a trustor (the subject that trusts a target entity) and a trustee (the entity that is trusted). In the context of social media, trust provides evidence about with whom we can trust to share information and from whom we can accept information without additional verification. With trust, we make the mental shortcut by directly seeking information from trustees or trusted entities, which serves a two-fold purpose: without being overwhelmed by excessive information (i.e., mitigated information overload) and with credible information due to the trust placed on the information provider (i.e., increased information credibility). Therefore, trust is crucial in helping social media users collect relevant and reliable information, and trust in social media is a research topic of increasing importance and of practical significance. This book takes a computational perspective to offer an overview of characteristics and elements of trust and illuminate a wide range of computational tasks of trust. It introduces basic concepts, deliberates challenges and opportunities, reviews state-of-the-art algorithms, and elaborates effective evaluation methods in the trust study. In particular, we illustrate properties and representation models of trust, elucidate trust prediction with representative algorithms, and demonstrate real-world applications where trust is explicitly used. As a new dimension of the trust study, we discuss the concept of distrust and its roles in trust computing.

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.

This book is the second of three volumes that illustrate the concept of social networks from a computational point of view. The book contains contributions from a international selection of world-class experts, concentrating on topics relating to security and privacy (the other two volumes review Tools, Perspectives, and Applications, and Mining and Visualization in CSNs). Topics and features: presents the latest advances in security and privacy issues in CSNs, and illustrates how both organizations and individuals can be protected from real-world threats; discusses the design and use of a wide range of computational tools and software for social network analysis; describes simulations of social networks, and the representation and analysis of social networks, with a focus on issues of security, privacy, and anonymization; provides experience reports, survey articles, and intelligence techniques and theories relating to specific problems in network technology.

This book focuses on three emerging research topics in mobile social networks (MSNs): privacy-preserving profile matching (PPM) protocols, privacy-preserving cooperative data forwarding (PDF) protocols, and trustworthy service evaluation (TSE) systems. The PPM helps two users compare their personal profiles without disclosing the profiles. The PDF helps users forward data to their friends via multiple cooperative relay peers while preserving their identity and location privacy. The TSE enables users to locally share service reviews on the vendors such that users receive more valuable information about the services not only from vendors but also from their trusted social friends. The authors address both theoretic and practical aspects of these topics by introducing the system model, reviewing the related works, and presenting the solutions. Security and Privacy for Mobile Social Networks further provides the security analysis and the performance evaluation based on real-trace simulations. It also summarizes the future research directions for this rapidly growing area of research. The book will be valuable for researchers and practitioners who work with mobile social networks, communication platforms, wireless communication techniques, and internet applications. "Suitable for any type of reader as an introduction to the topic... The chapters are well motivated and presented... It is recommended for researchers." -ACM Computing Reviews, 21 July 2014

Security and Privacy in Social Networks brings to the forefront innovative approaches for analyzing and enhancing the security and privacy dimensions in online social networks, and is the first comprehensive attempt dedicated entirely to this field. In order to facilitate the transition of such methods from theory to mechanisms designed and deployed in existing online social networking services, the book aspires to create a common language between the researchers and practitioners of this new area- spanning from the theory of computational social sciences to conventional security and network engineering.

Analyzing and Securing Social Networks focuses on the two major technologies that have been developed for online social networks (OSNs): (i) data mining technologies for analyzing these networks and extracting useful information such as location, demographics, and sentiments of the participants of the network, and (ii) security and privacy technolo

In recent years, virtual meeting technology has become a part of the everyday lives of more and more people, often with the help of global online social networks (OSNs). These help users to build both social and professional links on a worldwide scale. The sharing of information and opinions are important features of OSNs. Users can describe recent activities and interests, share photos, videos, applications, and much more. The use of OSNs has increased at a rapid rate. Google+, Facebook, Twitter, LinkedIn, Sina Weibo, VKontakte, and Mixi are all OSNs that have become the preferred way of communication for a vast number of daily active users. Users spend substantial amounts of time updating their information, communicating with other users, and browsing one another’s accounts. OSNs obliterate geographical distance and can breach economic barrier. This popularity has made OSNs a fascinating test bed for cyberattacks comprising Cross-Site Scripting, SQL injection, DDoS, phishing, spamming, fake profile, spammer, etc. OSNs security: Principles, Algorithm, Applications, and Perspectives describe various attacks, classifying them, explaining their consequences, and offering. It also highlights some key contributions related to the current defensive approaches. Moreover, it shows how machine-learning and deep-learning methods can mitigate attacks on OSNs. Different technological solutions that have been proposed are also discussed. The topics, methodologies, and outcomes included in this book will help readers learn the importance of incentives in any technical solution to handle attacks against OSNs. The best practices and guidelines will show how to implement various attack-mitigation methodologies.