This book highlights several gaps that have not been addressed in existing cyber security research. It first discusses the recent attack prediction techniques that utilize one or more aspects of information to create attack prediction models. The second part is dedicated to new trends on information fusion and their applicability to cyber security; in particular, graph data analytics for cyber security, unwanted traffic detection and control based on trust management software defined networks, security in wireless sensor networks & their applications, and emerging trends in security system design using the concept of social behavioral biometric. The book guides the design of new commercialized tools that can be introduced to improve the accuracy of existing attack prediction models. Furthermore, the book advances the use of Knowledge-based Intrusion Detection Systems (IDS) to complement existing IDS technologies. It is aimed towards cyber security researchers.

As the world becomes increasingly connected, it is also more exposed to a myriad of cyber threats. We need to use multiple types of tools and techniques to learn and understand the evolving threat landscape. Data is a common thread linking various types of devices and end users. Analyzing data across different segments of cybersecurity domains, particularly data generated during cyber-attacks, can help us understand threats better, prevent future cyber-attacks, and provide insights into the evolving cyber threat landscape. This book takes a data oriented approach to studying cyber threats, showing in depth how traditional methods such as anomaly detection can be extended using data analytics and also applies data analytics to non-traditional views of cybersecurity, such as multi domain analysis, time series and spatial data analysis, and human-centered cybersecurity.

This book introduces readers to the tools needed to protect IT resources and communicate with security specialists when there is a security problem. The book covers a wide range of security topics including Cryptographic Technologies, Network Security, Security Management, Information Assurance, Security Applications, Computer Security, Hardware Security, and Biometrics and Forensics. It introduces the concepts, techniques, methods, approaches, and trends needed by security specialists to improve their security skills and capabilities. Further, it provides a glimpse into future directions where security techniques, policies, applications, and theories are headed. The book represents a collection of carefully selected and reviewed chapters written by diverse security experts in the listed fields and edited by prominent security researchers. Complementary slides are available for download on the book’s website at Springer.com.

This book encompasses a systematic exploration of Cybersecurity Data Science (CSDS) as an emerging profession, focusing on current versus idealized practice. This book also analyzes challenges facing the emerging CSDS profession, diagnoses key gaps, and prescribes treatments to facilitate advancement. Grounded in the management of information systems (MIS) discipline, insights derive from literature analysis and interviews with 50 global CSDS practitioners. CSDS as a diagnostic process grounded in the scientific method is emphasized throughout Cybersecurity Data Science (CSDS) is a rapidly evolving discipline which applies data science methods to cybersecurity challenges. CSDS reflects the rising interest in applying data-focused statistical, analytical, and machine learning-driven methods to address growing security gaps. This book offers a systematic assessment of the developing domain. Advocacy is provided to strengthen professional rigor and best practices in the emerging CSDS profession. This book will be of interest to a range of professionals associated with cybersecurity and data science, spanning practitioner, commercial, public sector, and academic domains. Best practices framed will be of interest to CSDS practitioners, security professionals, risk management stewards, and institutional stakeholders. Organizational and industry perspectives will be of interest to cybersecurity analysts, managers, planners, strategists, and regulators. Research professionals and academics are presented with a systematic analysis of the CSDS field, including an overview of the state of the art, a structured evaluation of key challenges, recommended best practices, and an extensive bibliography.

This book constitutes the proceedings of the Second International Conference on Machine Learning for Cyber Security, ML4CS 2019, held in Xian, China in September 2019. The 23 revised full papers and 3 short papers presented were carefully reviewed and selected from 70 submissions. The papers detail all aspects of machine learning in network infrastructure security, in network security detections and in application software security.

This book constitutes the proceedings of the Second International Conference on Machine Learning for Cyber Security, ML4CS 2019, held in Xi’an, China in September 2019. The 23 revised full papers and 3 short papers presented were carefully reviewed and selected from 70 submissions. The papers detail all aspects of machine learning in network infrastructure security, in network security detections and in application software security.

This book constitutes the proceedings of the 4th International Conference on Science of Cyber Security, SciSec 2022, held in Matsu, Japan in August 2022. The 36 full papers presented in this volume were carefully reviewed and selected from 88 submissions. The papers are organized in the following topical sections: blockchain and applications; cryptography and applications; network security; cyber-physical system; malware; mobile system security; system and web security; security in financial industry; social engineering and personalized security; privacy and anonymity.

In recent years, industries have transitioned into the digital realm, as companies and organizations are adopting certain forms of technology to assist in information storage and efficient methods of production. This dependence has significantly increased the risk of cyber crime and breaches in data security. Fortunately, research in the area of cyber security and information protection is flourishing; however, it is the responsibility of industry professionals to keep pace with the current trends within this field. The Handbook of Research on Cyber Crime and Information Privacy is a collection of innovative research on the modern methods of crime and misconduct within cyber space. It presents novel solutions to securing and preserving digital information through practical examples and case studies. While highlighting topics including virus detection, surveillance technology, and social networks, this book is ideally designed for cybersecurity professionals, researchers, developers, practitioners, programmers, computer scientists, academicians, security analysts, educators, and students seeking up-to-date research on advanced approaches and developments in cyber security and information protection.

This book presents the outcomes of the 2020 International Conference on Cyber Security Intelligence and Analytics (CSIA 2020), which was dedicated to promoting novel theoretical and applied research advances in the interdisciplinary field of cyber security, particularly those focusing on threat intelligence, analytics, and preventing cyber crime. The conference provides a forum for presenting and discussing innovative ideas, cutting-edge research findings, and novel techniques, methods, and applications concerning all aspects of cyber security intelligence and analytics. CSIA 2020, which was held in Haikou, China on February 28–29, 2020, built on the previous conference in Wuhu, China (2019), and marks the series’ second successful installment.

In today’s globalized world, businesses and governments rely heavily on technology for storing and protecting essential information and data. Despite the benefits that computing systems offer, there remains an assortment of issues and challenges in maintaining the integrity and confidentiality of these databases. As professionals become more dependent cyberspace, there is a need for research on modern strategies and concepts for improving the security and safety of these technologies. Modern Theories and Practices for Cyber Ethics and Security Compliance is a collection of innovative research on the concepts, models, issues, challenges, innovations, and mitigation strategies needed to improve cyber protection. While highlighting topics including database governance, cryptography, and intrusion detection, this book provides guidelines for the protection, safety, and security of business data and national infrastructure from cyber-attacks. It is ideally designed for security analysts, law enforcement, researchers, legal practitioners, policymakers, business professionals, governments, strategists, educators, and students seeking current research on combative solutions for cyber threats and attacks.