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.

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.

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.

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 9th Multidisciplinary Academic Conference in Prague 2017, Czech Republic

The book covers tools in the study of online social networks such as machine learning techniques, clustering, and deep learning. A variety of theoretical aspects, application domains, and case studies for analyzing social network data are covered. The aim is to provide new perspectives on utilizing machine learning and related scientific methods and techniques for social network analysis. Machine Learning Techniques for Online Social Networks will appeal to researchers and students in these fields.

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 constitutes revised and selected papers from the 7th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2021, held in Fuzhou, China, in November 2021. The 16 full papers presented in this volume were carefully reviewed and selected from a total of 41 submissions. Such themes as privacy protection, security of AI, mobile social networks, Big Data system, applied cryptography, and others are covered in the volume.The papers are organized in the following topical sections: Applied Cryptography for Big Data; Big Data System Security; Forensics in Social Networks and Big Data; Privacy Protection in Social Networks; Security and Privacy in Big Database; Security of AI; Trust and Reputations in Social Networks.

Recently, mobile security has garnered considerable interest in both the research community and industry due to the popularity of smartphones. The current smartphone platforms are open systems that allow application development, also for malicious parties. To protect the mobile device, its user, and other mobile ecosystem stakeholders such as network operators, application execution is controlled by a platform security architecture. This book explores how such mobile platform security architectures work. We present a generic model for mobile platform security architectures: the model illustrates commonly used security mechanisms and techniques in mobile devices and allows a systematic comparison of different platforms. We analyze several mobile platforms using the model. In addition, this book explains hardware-security mechanisms typically present in a mobile device. We also discuss enterprise security extensions for mobile platforms and survey recent research in the area of mobile platform security. The objective of this book is to provide a comprehensive overview of the current status of mobile platform security for students, researchers, and practitioners.