This book presents recent developments on the theoretical, algorithmic, and application aspects of Big Data in Complex and Social Networks. The book consists of four parts, covering a wide range of topics. The first part of the book focuses on data storage and data processing. It explores how the efficient storage of data can fundamentally support intensive data access and queries, which enables sophisticated analysis. It also looks at how data processing and visualization help to communicate information clearly and efficiently. The second part of the book is devoted to the extraction of essential information and the prediction of web content. The book shows how Big Data analysis can be used to understand the interests, location, and search history of users and provide more accurate predictions of User Behavior. The latter two parts of the book cover the protection of privacy and security, and emergent applications of big data and social networks. It analyzes how to model rumor diffusion, identify misinformation from massive data, and design intervention strategies. Applications of big data and social networks in multilayer networks and multiparty systems are also covered in-depth.

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.

This book constitutes revised and selected papers from the 6th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2020, held in Tianjin, China, in September 2020. The 38 full papers presented in this volume were carefully reviewed and selected from a total of 111 submissions. The papers are organized according to the topical sections on big data security; social networks; privacy-preserving and security.

This book constitutes the proceedings of the 9th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2023, which took place in Canterbury, UK, in August 2023. The 10 full papers and 4 short papers presented in this volume were carefully reviewed and selected from 29 submissions. They were organized in topical sections as follows: information abuse and political discourse; attacks; social structure and community; and security and privacy matters. Papers "Data Reconstruction Attack Against Principal Component Analysis" and "Edge local Differential Privacy for Dynamic Graphs" are published Open Access under the CC BY 4.0 License.

This book constitutes the proceedings of the 8th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2022, which took place in Xi'an, China, in October 2022. The 23 papers presented in this volume were carefully reviewed and selected from 103 submissions. The papers were evaluated on the basis of their significance, novelty, technical quality, as well as on their practical impact or their level of advancement of the field’s foundations. They were organized in topical sections as follows: Cryptography and its applications; Network security and privacy protection; Data detection; Blockchain and its applications.

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.

This book constitutes revised and selected papers from the 5th International Symposium on Security and Privacy in Social Networks and Big Data, SocialSec 2019, held in Copenhagen, Denmark, in July 2019. The 18 full papers and 3 short papers presented in this volume were carefully reviewed and selected from a total of 76 submissions. The papers in the volume cover a broad range of topics on security in Internet-of-things, Social Networks, User Authentication, Algorithm design, Artificial Intelligence, and Big Data.

In recent years, technological advances have led to significant developments within a variety of business applications. In particular, data-driven research provides ample opportunity for enterprise growth, if utilized efficiently. Privacy and Security Policies in Big Data is a pivotal reference source for the latest research on innovative concepts on the management of security and privacy analytics within big data. Featuring extensive coverage on relevant areas such as kinetic knowledge, cognitive analytics, and parallel computing, this publication is an ideal resource for professionals, researchers, academicians, advanced-level students, and technology developers in the field of big data.

As big data becomes increasingly pervasive and cloud computing utilization becomes the norm, the security and privacy of our systems and data becomes more critical with emerging security and privacy threats and challenges. This book presents a comprehensive view on how to advance security and privacy in big data, cloud computing, and their applications. Topics include cryptographic tools, SDN security, big data security in IoT, privacy preserving in big data, security architecture based on cyber kill chain, privacy-aware digital forensics, trustworthy computing, privacy verification based on machine learning, and chaos-based communication systems. This book is an essential reading for networking, computing, and communications professionals, researchers, students and engineers, working with big data and cloud computing.

It is essential for an organization to know before involving themselves in cloud computing and big data, what are the key security requirements for applications and data processing. Big data and cloud computing are integrated together in practice. Cloud computing offers massive storage, high computation power, and distributed capability to support processing of big data. In such an integrated environment the security and privacy concerns involved in both technologies become combined. This book discusses these security and privacy issues in detail and provides necessary insights into cloud computing and big data integration. It will be useful in enhancing the body of knowledge concerning innovative technologies offered by the research community in the area of cloud computing and big data. Readers can get a better understanding of the basics of cloud computing, big data, and security mitigation techniques to deal with current challenges as well as future research opportunities.