Our world is increasingly driven by sophisticated networks of advanced computing technology, and the basic operation of everyday society is becoming increasingly vulnerable to these networks’ shortcomings. The implementation and upkeep of a strong network defense is a substantial challenge, beset not only by economic disincentives but also by an inherent logistical bias that grants advantage to attackers. Research Anthology on Combating Denial-of-Service Attacks examines the latest research on the development of intrusion detection systems and best practices for preventing and combatting cyber-attacks intended to disrupt business and user experience. Highlighting a range of topics such as network administration, application-layer protocols, and malware detection, this publication is an ideal reference source for cybersecurity professionals, IT specialists, policymakers, forensic analysts, technology developers, security administrators, academicians, researchers, and students.

The advent of the internet and social media were landmarks in furthering communication technologies. Through social media websites, families, friends, and communities could connect in a way never seen. Though these websites are helpful tools in facilitating positive interaction, they have also allowed users to verbally attack and bully each other with no fear of repercussion. Moreover, online predators will often use these tools to harass, stalk, and in some cases even lure their victims. Particularly rampant among adolescents, these harmful actions must be mitigated in order to safeguard the mental health and physical safety of users. The Research Anthology on Combating Cyber-Aggression and Online Negativity discusses the research behind cyber-aggression and cyber bullying, as well as methods to predict and prevent online negativity. It presents policy, technological, and human intervention practices against cyber-aggression. Covering topics such as media literacy, demographic variables, and workplace cyberbullying, this major reference work is a critical resource for students and educators of higher education, libraries, social media administrators, government organizations, K-12 teachers, computer scientists, sociologists, psychologists, human resource managers, researchers, and academicians.

The rise of technology has proven to be a threat to personal data, cyberspace protection, and organizational security. However, these technologies can be used to enhance the effectiveness of institutional security. Through the use of blockchain and the internet of things (IoT), organizations may combat cybercriminals and better protect their privacy. The Research Anthology on Convergence of Blockchain, Internet of Things, and Security describes the implementation of blockchain and IoT technologies to better protect personal and organizational data as well as enhance overall security. It also explains the tools, applications, and emerging innovations in security and the ways in which they are enhanced by blockchain and IoT. Covering topics such as electronic health records, intrusion detection, and software engineering, this major reference work is an essential resource for business leaders and executives, IT managers, computer scientists, hospital administrators, security professionals, law enforcement, students and faculty of higher education, librarians, researchers, and academicians.

In recent years, smart devices have become commonplace in our daily lives. On the internet of things (IoT), these devices powered new intelligent services. Their application enabled the rise of intelligent cities, smart agriculture, and Industry 4.0. However, smart devices collect and share large amounts of data, including the habits and preferences of their users. Cybersecurity incidents in intelligent environments may impact services used by millions across the world and make private information public. Information Security and Privacy in Smart Devices: Tools, Methods, and Applications presents research challenges, innovative insights, and trends related to solutions, methods, processes, and applications for maintaining information security and privacy in intelligent environments. Covering topics such as information retrieval methods, electronic health records, and misinformation detection, this premier reference source is an excellent resource for security professionals, government officials, business leaders and executives, IT managers, hospital administrators, students of higher education, librarians, researchers, and academicians.

This book constitutes the refereed post-conference proceedings of the 6th IFIP International Cross-Domain Conference on Internet of Things, IFIPIoT 2023, held in Denton, TX, USA, in November 2023. The 36 full papers and 27 short papers presented were carefully reviewed and selected from 84 submissions. The papers offer insights into the latest innovations, challenges, and opportunities in IoT, covering a wide array of topics, including IoT architectures, security and privacy, data analytics, edge computing, and applications in various domains.

Distributed Denial of Service (DDoS) attacks have become more destructive, wide-spread and harder to control over time. This book allows students to understand how these attacks are constructed, the security flaws they leverage, why they are effective, how they can be detected, and how they can be mitigated. Students use software defined networking (SDN) technology to created and execute controlled DDoS experiments. They learn how to deploy networks, analyze network performance, and create resilient systems. This book is used for graduate level computer engineering instruction at Clemson University. It augments the traditional graduate computing curricula by integrating: Internet deployment, network security, ethics, contemporary social issues, and engineering principles into a laboratory based course of instruction. Unique features of this book include: · A history of DDoS attacks that includes attacker motivations; · Discussion of cyber-war, censorship, and Internet black-outs; · SDN based DDoS laboratory assignments; · Up-to-date review of current DDoS attack techniques and tools; · Review of the current laws that globally relate to DDoS; · Abuse of DNS, NTP, BGP and other parts of the global Internet infrastructure to attack networks; · Mathematics of Internet traffic measurement; · Game theory for DDoS resilience; and · Construction of content distribution systems that absorb DDoS attacks. This book assumes familiarity with computing, Internet design, appropriate background in mathematics, and some programming skills. It provides analysis and reference material for networking engineers and researchers. By increasing student knowledge in security, and networking; it adds breadth and depth to advanced computing curricula.

With new technologies, such as computer vision, internet of things, mobile computing, e-governance and e-commerce, and wide applications of social media, organizations generate a huge volume of data and at a much faster rate than several years ago. Big data in large-/small-scale systems, characterized by high volume, diversity, and velocity, increasingly drives decision making and is changing the landscape of business intelligence. From governments to private organizations, from communities to individuals, all areas are being affected by this shift. There is a high demand for big data analytics that offer insights for computing efficiency, knowledge discovery, problem solving, and event prediction. To handle this demand and this increase in big data, there needs to be research on innovative and optimized machine learning algorithms in both large- and small-scale systems. Applications of Big Data in Large- and Small-Scale Systems includes state-of-the-art research findings on the latest development, up-to-date issues, and challenges in the field of big data and presents the latest innovative and intelligent applications related to big data. This book encompasses big data in various multidisciplinary fields from the medical field to agriculture, business research, and smart cities. While highlighting topics including machine learning, cloud computing, data visualization, and more, this book is a valuable reference tool for computer scientists, data scientists and analysts, engineers, practitioners, stakeholders, researchers, academicians, and students interested in the versatile and innovative use of big data in both large-scale and small-scale systems.