Privacy Risk Analysis Of Online Social Networks

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.

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.

The relentless growth of cyber threats poses an escalating challenge to our global community. The current landscape of cyber threats demands a proactive approach to cybersecurity, as the consequences of lapses in digital defense reverberate across industries and societies. From data breaches to sophisticated malware attacks, the vulnerabilities in our interconnected systems are glaring. As we stand at the precipice of a digital revolution, the need for a comprehensive understanding of cybersecurity risks and effective countermeasures has never been more pressing. Risk Assessment and Countermeasures for Cybersecurity is a book that clarifies many of these challenges in the realm of cybersecurity. It systematically navigates the web of security challenges, addressing issues that range from cybersecurity risk assessment to the deployment of the latest security countermeasures. As it confronts the threats lurking in the digital shadows, this book stands as a catalyst for change, encouraging academic scholars, researchers, and cybersecurity professionals to collectively fortify the foundations of our digital world.

This book constitutes the revised selected papers from the 12th International Conference on Risk and Security of Internet and Systems, CRISIS 2017, held in Dinard, France, in September 2017.The 12 full papers and 5 short papers presented in this volume were carefully reviewed and selected from 42 submissions. They cover diverse research themes, ranging from classic topics, such as vulnerability analysis and classification; apps security; access control and filtering; cloud security; cyber-insurance and cyber threat intelligence; human-centric security and trust; and risk analysis.

This synthesis lecture provides a survey of work on privacy in online social networks (OSNs). This work encompasses concerns of users as well as service providers and third parties. Our goal is to approach such concerns from a computer-science perspective, and building upon existing work on privacy, security, statistical modeling and databases to provide an overview of the technical and algorithmic issues related to privacy in OSNs. We start our survey by introducing a simple OSN data model and describe common statistical-inference techniques that can be used to infer potentially sensitive information. Next, we describe some privacy definitions and privacy mechanisms for data publishing. Finally, we describe a set of recent techniques for modeling, evaluating, and managing individual users' privacy risk within the context of OSNs. Table of Contents: Introduction / A Model for Online Social Networks / Types of Privacy Disclosure / Statistical Methods for Inferring Information in Networks / Anonymity and Differential Privacy / Attacks and Privacy-preserving Mechanisms / Models of Information Sharing / Users' Privacy Risk / Management of Privacy Settings

This book constitutes the refereed proceedings of the 4th International Conference on Big Data and Security, ICBDS 2022, held in Xiamen, China, during December 8–12, 2022. The 51 full papers and 3 short papers included in this book were carefully reviewed and selected from 211 submissions. They were organized in topical sections as follows: answer set programming; big data and new method; intelligence and machine learning security; data technology and network security; sybersecurity and privacy; IoT security.

The present volume provides a comprehensive resource for practitioners and researchers alike-both those new to the field as well as those who already have some experience. The work covers Social Network Analysis theory and methods with a focus on current applications and case studies applied in various domains such as mobile networks, security, machine learning and health. With the increasing popularity of Web 2.0, social media has become a widely used communication platform. Parallel to this development, Social Network Analysis gained in importance as a research field, while opening up many opportunities in different application domains. Forming a bridge between theory and applications makes this work appealing to both academics and practitioners as well as graduate students.