Security And Privacy Preserving In Social Networks

This volume aims at assessing the current approaches and technologies, as well as to outline the major challenges and future perspectives related to the security and privacy protection of social networks. It provides the reader with an overview of the state-of-the art techniques, studies, and approaches as well as outlining future directions in this field. A wide range of interdisciplinary contributions from various research groups ensures for a balanced and complete perspective.

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.

As industries are rapidly being digitalized and information is being more heavily stored and transmitted online, the security of information has become a top priority in securing the use of online networks as a safe and effective platform. With the vast and diverse potential of artificial intelligence (AI) applications, it has become easier than ever to identify cyber vulnerabilities, potential threats, and the identification of solutions to these unique problems. The latest tools and technologies for AI applications have untapped potential that conventional systems and human security systems cannot meet, leading AI to be a frontrunner in the fight against malware, cyber-attacks, and various security issues. However, even with the tremendous progress AI has made within the sphere of security, it’s important to understand the impacts, implications, and critical issues and challenges of AI applications along with the many benefits and emerging trends in this essential field of security-based research. Research Anthology on Artificial Intelligence Applications in Security seeks to address the fundamental advancements and technologies being used in AI applications for the security of digital data and information. The included chapters cover a wide range of topics related to AI in security stemming from the development and design of these applications, the latest tools and technologies, as well as the utilization of AI and what challenges and impacts have been discovered along the way. This resource work is a critical exploration of the latest research on security and an overview of how AI has impacted the field and will continue to advance as an essential tool for security, safety, and privacy online. This book is ideally intended for cyber security analysts, computer engineers, IT specialists, practitioners, stakeholders, researchers, academicians, and students interested in AI applications in the realm of security research.

Mobile technologies have become a staple in society for their accessibility and diverse range of applications that are continually growing and advancing. Users are increasingly using these devices for activities beyond simple communication including gaming and e-commerce and to access confidential information including banking accounts and medical records. While mobile devices are being so widely used and accepted in daily life, and subsequently housing more and more personal data, it is evident that the security of these devices is paramount. As mobile applications now create easy access to personal information, they can incorporate location tracking services, and data collection can happen discreetly behind the scenes. Hence, there needs to be more security and privacy measures enacted to ensure that mobile technologies can be used safely. Advancements in trust and privacy, defensive strategies, and steps for securing the device are important foci as mobile technologies are highly popular and rapidly developing. The Research Anthology on Securing Mobile Technologies and Applications discusses the strategies, methods, and technologies being employed for security amongst mobile devices and applications. This comprehensive book explores the security support that needs to be required on mobile devices to avoid application damage, hacking, security breaches and attacks, or unauthorized accesses to personal data. The chapters cover the latest technologies that are being used such as cryptography, verification systems, security policies and contracts, and general network security procedures along with a look into cybercrime and forensics. This book is essential for software engineers, app developers, computer scientists, security and IT professionals, practitioners, stakeholders, researchers, academicians, and students interested in how mobile technologies and applications are implementing security protocols and tactics amongst devices.

Advances in hardware technology have increased the capability to store and record personal data. This has caused concerns that personal data may be abused. This book proposes a number of techniques to perform the data mining tasks in a privacy-preserving way. This edited volume contains surveys by distinguished researchers in the privacy field. Each survey includes the key research content as well as future research directions of a particular topic in privacy. The book is designed for researchers, professors, and advanced-level students in computer science, but is also suitable for practitioners in industry.

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

This book introduces the state-of-the-art algorithms for data and computation privacy. It mainly focuses on searchable symmetric encryption algorithms and privacy preserving multi-party computation algorithms. This book also introduces algorithms for breaking privacy, and gives intuition on how to design algorithm to counter privacy attacks. Some well-designed differential privacy algorithms are also included in this book. Driven by lower cost, higher reliability, better performance, and faster deployment, data and computing services are increasingly outsourced to clouds. In this computing paradigm, one often has to store privacy sensitive data at parties, that cannot fully trust and perform privacy sensitive computation with parties that again cannot fully trust. For both scenarios, preserving data privacy and computation privacy is extremely important. After the Facebook–Cambridge Analytical data scandal and the implementation of the General Data Protection Regulation by European Union, users are becoming more privacy aware and more concerned with their privacy in this digital world. This book targets database engineers, cloud computing engineers and researchers working in this field. Advanced-level students studying computer science and electrical engineering will also find this book useful as a reference or secondary text.

Managing and Mining Graph Data is a comprehensive survey book in graph management and mining. It contains extensive surveys on a variety of important graph topics such as graph languages, indexing, clustering, data generation, pattern mining, classification, keyword search, pattern matching, and privacy. It also studies a number of domain-specific scenarios such as stream mining, web graphs, social networks, chemical and biological data. The chapters are written by well known researchers in the field, and provide a broad perspective of the area. This is the first comprehensive survey book in the emerging topic of graph data processing. Managing and Mining Graph Data is designed for a varied audience composed of professors, researchers and practitioners in industry. This volume is also suitable as a reference book for advanced-level database students in computer science and engineering.