AI-Driven Cybersecurity andThreat Intelligence PDF Download

Author: Iqbal H. Sarker
Publisher: Springer Nature
ISBN: 3031544978
Category :
Languages : en
Pages : 207

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Book Description

Author: Iqbal H. Sarker
Publisher: Springer
ISBN: 9783031544965
Category : Computers
Languages : en
Pages : 0

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Book Description
This book explores the dynamics of how AI (Artificial Intelligence) technology intersects with cybersecurity challenges and threat intelligence as they evolve. Integrating AI into cybersecurity not only offers enhanced defense mechanisms, but this book introduces a paradigm shift illustrating how one conceptualize, detect and mitigate cyber threats. An in-depth exploration of AI-driven solutions is presented, including machine learning algorithms, data science modeling, generative AI modeling, threat intelligence frameworks and Explainable AI (XAI) models. As a roadmap or comprehensive guide to leveraging AI/XAI to defend digital ecosystems against evolving cyber threats, this book provides insights, modeling, real-world applications and research issues. Throughout this journey, the authors discover innovation, challenges, and opportunities. It provides a holistic perspective on the transformative role of AI in securing the digital world. Overall, the use of AI can transform the way one detects, responds and defends against threats, by enabling proactive threat detection, rapid response and adaptive defense mechanisms. AI-driven cybersecurity systems excel at analyzing vast datasets rapidly, identifying patterns that indicate malicious activities, detecting threats in real time as well as conducting predictive analytics for proactive solution. Moreover, AI enhances the ability to detect anomalies, predict potential threats, and respond swiftly, preventing risks from escalated. As cyber threats become increasingly diverse and relentless, incorporating AI/XAI into cybersecurity is not just a choice, but a necessity for improving resilience and staying ahead of ever-changing threats. This book targets advanced-level students in computer science as a secondary textbook. Researchers and industry professionals working in various areas, such as Cyber AI, Explainable and Responsible AI, Human-AI Collaboration, Automation and Intelligent Systems, Adaptive and Robust Security Systems, Cybersecurity Data Science and Data-Driven Decision Making will also find this book useful as reference book.

Author: Yassine Maleh
Publisher: CRC Press
ISBN: 1000846695
Category : Computers
Languages : en
Pages : 310

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Book Description
In recent years, a considerable amount of effort has been devoted to cyber-threat protection of computer systems which is one of the most critical cybersecurity tasks for single users and businesses since even a single attack can result in compromised data and sufficient losses. Massive losses and frequent attacks dictate the need for accurate and timely detection methods. Current static and dynamic methods do not provide efficient detection, especially when dealing with zero-day attacks. For this reason, big data analytics and machine intelligencebased techniques can be used. This book brings together researchers in the field of big data analytics and intelligent systems for cyber threat intelligence CTI and key data to advance the mission of anticipating, prohibiting, preventing, preparing, and responding to internal security. The wide variety of topics it presents offers readers multiple perspectives on various disciplines related to big data analytics and intelligent systems for cyber threat intelligence applications. Technical topics discussed in the book include: • Big data analytics for cyber threat intelligence and detection • Artificial intelligence analytics techniques • Real-time situational awareness • Machine learning techniques for CTI • Deep learning techniques for CTI • Malware detection and prevention techniques • Intrusion and cybersecurity threat detection and analysis • Blockchain and machine learning techniques for CTI

Author: Ali Dehghantanha
Publisher: Springer
ISBN: 3319739514
Category : Computers
Languages : en
Pages : 334

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Book Description
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.

Author: Leslie F. Sikos
Publisher: Springer Nature
ISBN: 3030387887
Category : Computers
Languages : en
Pages : 140

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Book Description
This book presents a collection of state-of-the-art approaches to utilizing machine learning, formal knowledge bases and rule sets, and semantic reasoning to detect attacks on communication networks, including IoT infrastructures, to automate malicious code detection, to efficiently predict cyberattacks in enterprises, to identify malicious URLs and DGA-generated domain names, and to improve the security of mHealth wearables. This book details how analyzing the likelihood of vulnerability exploitation using machine learning classifiers can offer an alternative to traditional penetration testing solutions. In addition, the book describes a range of techniques that support data aggregation and data fusion to automate data-driven analytics in cyberthreat intelligence, allowing complex and previously unknown cyberthreats to be identified and classified, and countermeasures to be incorporated in novel incident response and intrusion detection mechanisms.

Author: Emmanuel Joseph
Publisher: Independently Published
ISBN:
Category :
Languages : en
Pages : 0

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Book Description
In a rapidly evolving digital landscape, the convergence of artificial intelligence (AI) and security presents both unprecedented opportunities and unforeseen challenges. "The Unforeseen Threat of AI on Security" delves deep into the complex and dynamic relationship between AI and cybersecurity, offering a comprehensive exploration of the critical issues that define this technological frontier. As AI continues to reshape the world, it simultaneously empowers cyber adversaries with unprecedented capabilities. This book navigates through the shadowy world of AI-driven threats, unveiling the dark side of machine learning, autonomous cyberattacks, and state-sponsored espionage. Through real-world case studies, it reveals the tangible consequences of AI infiltrating the security realm, from crippling ransomware attacks to sophisticated deepfake-driven scams. Amidst these challenges, "The Unforeseen Threat of AI on Security" also illuminates the defensive power of AI. It explores cutting-edge AI security technologies, from predictive threat intelligence to autonomous incident response, showcasing how AI is becoming a vital ally in the fight against evolving cyber threats. Furthermore, it dissects the evolving dynamics of human-machine collaboration in security, highlighting the pivotal role that humans play alongside AI in safeguarding digital ecosystems. Ethical considerations are woven throughout the narrative, as the book addresses the profound ethical dilemmas posed by AI in security, from privacy and bias to transparency and accountability. It delves into the evolving governance and policy frameworks that govern AI security practices, emphasizing the need for responsible and lawful AI deployment. Looking ahead, "The Unforeseen Threat of AI on Security" anticipates future trends in AI security, offering insights into AI-generated malware, quantum computing's impact on encryption, deepfake attacks, and the evolving role of AI in national security. This book is a must-read for cybersecurity professionals, policymakers, technologists, and anyone interested in the transformative power of AI in both shaping and safeguarding our digital future. It serves as a vital guide for navigating the intricate landscape of AI and security, where innovation and defense intersect, and where the unforeseen threats of AI are met with resilience, vigilance, and ethical responsibility.

Author: Shengjie Xu
Publisher: John Wiley & Sons
ISBN: 1119784123
Category : Computers
Languages : en
Pages : 148

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Book Description
CYBERSECURITY IN INTELLIGENT NETWORKING SYSTEMS Help protect your network system with this important reference work on cybersecurity Cybersecurity and privacy are critical to modern network systems. As various malicious threats have been launched that target critical online services—such as e-commerce, e-health, social networks, and other major cyber applications—it has become more critical to protect important information from being accessed. Data-driven network intelligence is a crucial development in protecting the security of modern network systems and ensuring information privacy. Cybersecurity in Intelligent Networking Systems provides a background introduction to data-driven cybersecurity, privacy preservation, and adversarial machine learning. It offers a comprehensive introduction to exploring technologies, applications, and issues in data-driven cyber infrastructure. It describes a proposed novel, data-driven network intelligence system that helps provide robust and trustworthy safeguards with edge-enabled cyber infrastructure, edge-enabled artificial intelligence (AI) engines, and threat intelligence. Focusing on encryption-based security protocol, this book also highlights the capability of a network intelligence system in helping target and identify unauthorized access, malicious interactions, and the destruction of critical information and communication technology. Cybersecurity in Intelligent Networking Systems readers will also find: Fundamentals in AI for cybersecurity, including artificial intelligence, machine learning, and security threats Latest technologies in data-driven privacy preservation, including differential privacy, federated learning, and homomorphic encryption Key areas in adversarial machine learning, from both offense and defense perspectives Descriptions of network anomalies and cyber threats Background information on data-driven network intelligence for cybersecurity Robust and secure edge intelligence for network anomaly detection against cyber intrusions Detailed descriptions of the design of privacy-preserving security protocols Cybersecurity in Intelligent Networking Systems is an essential reference for all professional computer engineers and researchers in cybersecurity and artificial intelligence, as well as graduate students in these fields.

Author: S. R. Jena
Publisher: Scholars' Press
ISBN: 3659840785
Category : Computers
Languages : en
Pages : 126

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Book Description
Welcome to the forefront of modern cyber security – a landscape shaped and transformed by the relentless evolution of Artificial Intelligence (AI) and Deep Learning technologies. As we stand at the precipice of the digital era, the need for robust, intelligent defense mechanisms against cyber threats has never been more pressing. This book, "AI-Driven Cyber Security: Navigating the Digital Frontier with Deep Learning" embarks on a comprehensive journey through the intricate realm where cutting-edge AI meets the ever-evolving challenges of cyber security. In the interconnected world we inhabit, where data is the lifeblood of every organisation, the marriage of AI and cyber security becomes not just a choice but a necessity. Moreover, the book contains 8 chapters. They are: 1. Introduction to Cyber Security 2. Foundations of Cyber Security 3. Basics of AI and Deep Learning 4. AI in Cyber Security: An Overview 5. Deep Learning for Threat Detection 6. Natural Language Processing (NLP) in Cyber Security 7. Adversarial Machine Learning 8. Explainability and Transparency in AI Security

Author: Kris Hermans
Publisher: Cybellium Ltd
ISBN:
Category : Computers
Languages : en
Pages : 95

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Book Description
In the rapidly evolving world of cybersecurity, the intersection of hacking and artificial intelligence (AI) has become an arena of immense potential. "Mastering Hacking with AI" by Kris Hermans is your comprehensive guide to harnessing the power of AI for ethical hacking purposes. This groundbreaking book takes you on a transformative journey, equipping you with the knowledge and skills to master the fusion of hacking and AI. Inside this groundbreaking book, you will: Explore the core principles of hacking and AI, including machine learning techniques, natural language processing, anomaly detection, and adversarial attacks, enabling you to develop advanced hacking strategies. Gain hands-on experience through real-world examples, step-by-step tutorials, and AI-driven tools, allowing you to apply AI techniques to identify vulnerabilities, automate penetration testing, and enhance threat intelligence. Understand the ethical implications of AI-driven hacking and learn how to responsibly use AI for cybersecurity purposes, adhering to legal and ethical frameworks. Stay ahead of the curve with discussions on emerging trends in AI and their impact on cybersecurity, such as AI-powered defences, deepfake detection, and autonomous threat hunting.

Author: Mark Stamp
Publisher: Springer Nature
ISBN: 3030970876
Category : Computers
Languages : en
Pages : 388

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Book Description
This book explores new and novel applications of machine learning, deep learning, and artificial intelligence that are related to major challenges in the field of cybersecurity. The provided research goes beyond simply applying AI techniques to datasets and instead delves into deeper issues that arise at the interface between deep learning and cybersecurity. This book also provides insight into the difficult "how" and "why" questions that arise in AI within the security domain. For example, this book includes chapters covering "explainable AI", "adversarial learning", "resilient AI", and a wide variety of related topics. It’s not limited to any specific cybersecurity subtopics and the chapters touch upon a wide range of cybersecurity domains, ranging from malware to biometrics and more. Researchers and advanced level students working and studying in the fields of cybersecurity (equivalently, information security) or artificial intelligence (including deep learning, machine learning, big data, and related fields) will want to purchase this book as a reference. Practitioners working within these fields will also be interested in purchasing this book.