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The rapid growth of the Internet interconnectivity and complexity of communication systems has led us to a significant growth of cyberattacks globally often with severe and disastrous consequences. The swift development of more innovative and effective (cyber)security solutions and approaches are vital which can detect, mitigate and prevent from these serious consequences. Cybersecurity is gaining momentum and is scaling up in very many areas. This book builds on the experience of the Cyber-Trust EU project's methods, use cases, technology development, testing and validation and extends into a broader science, lead IT industry market and applied research with practical cases. It offers new perspectives on advanced (cyber) security innovation (eco) systems covering key different perspectives. The book provides insights on new security technologies and methods for advanced cyber threat intelligence, detection and mitigation. We cover topics such as cyber-security and AI, cyber-threat intelligence, digital forensics, moving target defense, intrusion detection systems, post-quantum security, privacy and data protection, security visualization, smart contracts security, software security, blockchain, security architectures, system and data integrity, trust management systems, distributed systems security, dynamic risk management, privacy and ethics.
This book discusses national cyber threat intelligence and security information sharing. It details ongoing work in research laboratories world-wide to address current national security concerns. It allows practitioners to learn about upcoming trends, researchers to share current results, and decision makers to prepare for future developments.
Dive into the realm of cybersecurity with 'Cyber Threat Intelligence: Enhancing Security Through Proactive Detection.' This essential guide provides a comprehensive overview of cyber threat intelligence, empowering cybersecurity professionals and organizations to identify, mitigate, and prevent cyber threats effectively. From understanding threat actors and collection techniques to analyzing and applying intelligence for strategic decision-making, each chapter offers practical insights, methodologies, and real-world examples. Whether you're defending against sophisticated cyber attacks or enhancing your threat intelligence capabilities, this book serves as your indispensable companion in navigating the evolving landscape of cybersecurity.
This book provides readers with up-to-date research of emerging cyber threats and defensive mechanisms, which are timely and essential. It covers cyber threat intelligence concepts against a range of threat actors and threat tools (i.e. ransomware) in cutting-edge technologies, i.e., Internet of Things (IoT), Cloud computing and mobile devices. This book also provides the technical information on cyber-threat detection methods required for the researcher and digital forensics experts, in order to build intelligent automated systems to fight against advanced cybercrimes. The ever increasing number of cyber-attacks requires the cyber security and forensic specialists to detect, analyze and defend against the cyber threats in almost real-time, and with such a large number of attacks is not possible without deeply perusing the attack features and taking corresponding intelligent defensive actions – this in essence defines cyber threat intelligence notion. However, such intelligence would not be possible without the aid of artificial intelligence, machine learning and advanced data mining techniques to collect, analyze, and interpret cyber-attack campaigns which is covered in this book. This book will focus on cutting-edge research from both academia and industry, with a particular emphasis on providing wider knowledge of the field, novelty of approaches, combination of tools and so forth to perceive reason, learn and act on a wide range of data collected from different cyber security and forensics solutions. This book introduces the notion of cyber threat intelligence and analytics and presents different attempts in utilizing machine learning and data mining techniques to create threat feeds for a range of consumers. Moreover, this book sheds light on existing and emerging trends in the field which could pave the way for future works. The inter-disciplinary nature of this book, makes it suitable for a wide range of audiences with backgrounds in artificial intelligence, cyber security, forensics, big data and data mining, distributed systems and computer networks. This would include industry professionals, advanced-level students and researchers that work within these related fields.
Cyber-Security Threats, Actors, and Dynamic Mitigation provides both a technical and state-of-the-art perspective as well as a systematic overview of the recent advances in different facets of cyber-security. It covers the methodologies for modeling attack strategies used by threat actors targeting devices, systems, and networks such as smart homes, critical infrastructures, and industrial IoT. With a comprehensive review of the threat landscape, the book explores both common and sophisticated threats to systems and networks. Tools and methodologies are presented for precise modeling of attack strategies, which can be used both proactively in risk management and reactively in intrusion prevention and response systems. Several contemporary techniques are offered ranging from reconnaissance and penetration testing to malware detection, analysis, and mitigation. Advanced machine learning-based approaches are also included in the area of anomaly-based detection, that are capable of detecting attacks relying on zero-day vulnerabilities and exploits. Academics, researchers, and professionals in cyber-security who want an in-depth look at the contemporary aspects of the field will find this book of interest. Those wanting a unique reference for various cyber-security threats and how they are detected, analyzed, and mitigated will reach for this book often.
This book brings together the essential methodologies required to understand the advancement of digital technologies into digital transformation, as well as to protect them against cyber threat vulnerabilities (in this context cybersecurity attack ontology is included, modeling different types of adversary knowledge). It covers such essential methodologies as CIA Triad, Security Risk, Likelihood, and Consequence Level, Threat Attack Profiling, Threat Intelligence, Threat Lifecycle and more. The idea behind digital transformation is to use digital technologies not only to replicate an existing process in a digital form, but to use digital technology to transform that process into something intelligent (where anything is connected with everything at any time and accessible and controlled and designed advanced). Against this background, cyber threat attacks become reality, using advanced digital technologies with their extreme interconnected capability which call for sophisticated cybersecurity protecting digital technologies of digital transformation. Scientists, advanced-level students and researchers working in computer science, electrical engineering and applied mathematics will find this book useful as a reference guide. Professionals working in the field of big data analytics or digital/intelligent manufacturing will also find this book to be a valuable tool.
Develop the analytical skills to effectively safeguard your organization by enhancing defense mechanisms, and become a proficient threat intelligence analyst to help strategic teams in making informed decisions Key FeaturesBuild the analytics skills and practices you need for analyzing, detecting, and preventing cyber threatsLearn how to perform intrusion analysis using the cyber threat intelligence (CTI) processIntegrate threat intelligence into your current security infrastructure for enhanced protectionBook Description The sophistication of cyber threats, such as ransomware, advanced phishing campaigns, zero-day vulnerability attacks, and advanced persistent threats (APTs), is pushing organizations and individuals to change strategies for reliable system protection. Cyber Threat Intelligence converts threat information into evidence-based intelligence that uncovers adversaries' intents, motives, and capabilities for effective defense against all kinds of threats. This book thoroughly covers the concepts and practices required to develop and drive threat intelligence programs, detailing the tasks involved in each step of the CTI lifecycle. You'll be able to plan a threat intelligence program by understanding and collecting the requirements, setting up the team, and exploring the intelligence frameworks. You'll also learn how and from where to collect intelligence data for your program, considering your organization level. With the help of practical examples, this book will help you get to grips with threat data processing and analysis. And finally, you'll be well-versed with writing tactical, technical, and strategic intelligence reports and sharing them with the community. By the end of this book, you'll have acquired the knowledge and skills required to drive threat intelligence operations from planning to dissemination phases, protect your organization, and help in critical defense decisions. What you will learnUnderstand the CTI lifecycle which makes the foundation of the studyForm a CTI team and position it in the security stackExplore CTI frameworks, platforms, and their use in the programIntegrate CTI in small, medium, and large enterprisesDiscover intelligence data sources and feedsPerform threat modelling and adversary and threat analysisFind out what Indicators of Compromise (IoCs) are and apply the pyramid of pain in threat detectionGet to grips with writing intelligence reports and sharing intelligenceWho this book is for This book is for security professionals, researchers, and individuals who want to gain profound knowledge of cyber threat intelligence and discover techniques to prevent varying types of cyber threats. Basic knowledge of cybersecurity and network fundamentals is required to get the most out of this book.
Comprehensive resource providing strategic defense mechanisms for malware, handling cybercrime, and identifying loopholes using artificial intelligence (AI) and machine learning (ML) Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is a comprehensive look at state-of-the-art theory and practical guidelines pertaining to the subject, showcasing recent innovations, emerging trends, and concerns as well as applied challenges encountered, and solutions adopted in the fields of cybersecurity using analytics and machine learning. The text clearly explains theoretical aspects, framework, system architecture, analysis and design, implementation, validation, and tools and techniques of data science and machine learning to detect and prevent cyber threats. Using AI and ML approaches, the book offers strategic defense mechanisms for addressing malware, cybercrime, and system vulnerabilities. It also provides tools and techniques that can be applied by professional analysts to safely analyze, debug, and disassemble any malicious software they encounter. With contributions from qualified authors with significant experience in the field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection explores topics such as: Cybersecurity tools originating from computational statistics literature and pure mathematics, such as nonparametric probability density estimation, graph-based manifold learning, and topological data analysis Applications of AI to penetration testing, malware, data privacy, intrusion detection system (IDS), and social engineering How AI automation addresses various security challenges in daily workflows and how to perform automated analyses to proactively mitigate threats Offensive technologies grouped together and analyzed at a higher level from both an offensive and defensive standpoint Providing detailed coverage of a rapidly expanding field, Applying Artificial Intelligence in Cyber Security Analytics and Cyber Threat Detection is an essential resource for a wide variety of researchers, scientists, and professionals involved in fields that intersect with cybersecurity, artificial intelligence, and machine learning.