In an era defined by rapid technological advancements and an increasingly interconnected world, the challenges and opportunities presented by digitalization demand a new approach. The digital world, characterized by optimized, sustainable, and digitally networked solutions, necessitates the integration of intelligence systems, machine learning, deep learning, blockchain methods, and robust cybersecurity measures. Understanding these complex challenges and adapting the synergistic utilization of cutting-edge technologies are becoming increasingly necessary. Human Impact on Security and Privacy: Network and Human Security, Social Media, and Devices provides a global perspective on current and future trends concerning the integration of intelligent systems with cybersecurity applications. It offers a comprehensive exploration of ethical considerations within the realms of security, artificial intelligence, agriculture, and data science. Covering topics such as the evolving landscape of cybersecurity, social engineering perspectives, and algorithmic transparency, this publication is particularly valuable for researchers, industry professionals, academics, and policymakers in fields such as agriculture, cybersecurity, AI, data science, computer science, and ethics.

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.

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.

Surveys the rich and diverse landscape of privacy in HCI and CSCW, describing some of the legal foundations and historical aspects of privacy, sketching out an overview of the body of knowledge with respect to designing, implementing, and evaluating privacy-affecting systems, and charting many directions for future work.

Recently, the ICT field has seen a shift from machine-centered focuses to human and user knowledge-based approaches. However, as priorities shift, questions arise on how to detect and monitor users’ behavior. Human Behavior Recognition Technologies: Intelligent Applications for Monitoring and Security takes an insightful look into the applications and dependability of behavior detection. In addition, this comprehensive publication looks into the social, ethical, and legal implications of these areas. Researchers and practitioners interested in the computational aspects of behavior monitoring as well as the ethical and legal implications will find this reference source beneficial.

This book constructs a multidisciplinary approach to human security questions related to digitalisation in the European High North i.e. the northernmost areas of Scandinavia, Finland and North-Western Russia. It challenges the mainstream conceptualisation of cybersecurity and reconstructs it with the human being as the referent object of security.

This book covers topics needed to be considered in research around usable privacy. The book starts from a psychological perspective and introduces readers to basic behavioral theories and models that can explain end-user privacy behavior (including the “privacy paradox”) on a theoretical level. Subsequently, an introduction to different study methods (e.g., experiment, survey, interviews, co-creation) used in usable privacy research is given. Based on this, different methodological aspects, such as identifying appropriate questionnaires, and applying User-Centered Design, will be discussed. Finally, the book describes application areas for privacy research such as dark patterns and presents solutions for privacy protection, e.g., regarding consent-giving and PETs. The book aims to bring together the different research approaches to the topic of usable privacy, which often originate from computer science, psychology, and law, and provide a methodologically sound basis for researchers who want to delve deeper into this topic. This is an open access book.

Security in IoT Social Networks takes a deep dive into security threats and risks, focusing on real-world social and financial effects. Mining and analyzing enormously vast networks is a vital part of exploiting Big Data. This book provides insight into the technological aspects of modeling, searching, and mining for corresponding research issues, as well as designing and analyzing models for resolving such challenges. The book will help start-ups grow, providing research directions concerning security mechanisms and protocols for social information networks. The book covers structural analysis of large social information networks, elucidating models and algorithms and their fundamental properties. Moreover, this book includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models. This book is a detailed reference for academicians, professionals, and young researchers. The wide range of topics provides extensive information and data for future research challenges in present-day social information networks. - Provides several characteristics of social, network, and physical security associated with social information networks - Presents the security mechanisms and events related to social information networks - Covers emerging topics, such as network information structures like on-line social networks, heterogeneous and homogeneous information networks, and modern information networks - Includes smart solutions based on artificial intelligence, machine learning, and deep learning for enhancing the performance of social information network security protocols and models