AI and ML Applications for Decision-Making in Zero Trust Cyber Security
AI and ML Applications for Decision-Making in Zero Trust Cyber Security

Author: Dr Zemelak Goraga

Publisher: Skylimit Publishing

Published: 2024-04-03

Total Pages: 0

ISBN-13: 9785361564743

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Discover the future of cybersecurity with "AI and ML Applications for Decision-Making on Zero Trust Cyber Security: Volume 1." This groundbreaking book delves deep into the realm of Zero Trust Cyber Security, exploring the transformative potential of Artificial Intelligence (AI) and Machine Learning (ML) in fortifying digital defenses. Through insightful analysis and real-world case studies, this volume unveils how AI and ML technologies revolutionize decision-making processes, empowering organizations to adopt a proactive approach to cybersecurity. From advanced anomaly detection to behavioral analysis and threat intelligence, discover how these cutting-edge applications enhance authentication, authorization, and data protection mechanisms. Whether you're a cybersecurity professional, IT strategist, or technology enthusiast, this book provides invaluable insights into harnessing the power of AI and ML to combat evolving cyber threats. Stay ahead of the curve and secure your digital assets with the indispensable knowledge found within these pages.

Strategy, Leadership, and AI in the Cyber Ecosystem
Strategy, Leadership, and AI in the Cyber Ecosystem

Author: Hamid Jahankhani

Publisher: Academic Press

Published: 2020-11-10

Total Pages: 432

ISBN-13: 0128214597

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Strategy, Leadership and AI in the Cyber Ecosystem investigates the restructuring of the way cybersecurity and business leaders engage with the emerging digital revolution towards the development of strategic management, with the aid of AI, and in the context of growing cyber-physical interactions (human/machine co-working relationships). The book explores all aspects of strategic leadership within a digital context. It investigates the interactions from both the firm/organization strategy perspective, including cross-functional actors/stakeholders who are operating within the organization and the various characteristics of operating in a cyber-secure ecosystem. As consumption and reliance by business on the use of vast amounts of data in operations increase, demand for more data governance to minimize the issues of bias, trust, privacy and security may be necessary. The role of management is changing dramatically, with the challenges of Industry 4.0 and the digital revolution. With this intelligence explosion, the influence of artificial intelligence technology and the key themes of machine learning, big data, and digital twin are evolving and creating the need for cyber-physical management professionals. Discusses the foundations of digital societies in information governance and decision-making Explores the role of digital business strategies to deal with big data management, governance and digital footprints Considers advances and challenges in ethical management with data privacy and transparency Investigates the cyber-physical project management professional [Digital Twin] and the role of Holographic technology in corporate decision-making

AI and Machine Learning for Network and Security Management
AI and Machine Learning for Network and Security Management

Author: Yulei Wu

Publisher: John Wiley & Sons

Published: 2022-11-08

Total Pages: 308

ISBN-13: 1119835879

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AI AND MACHINE LEARNING FOR NETWORK AND SECURITY MANAGEMENT Extensive Resource for Understanding Key Tasks of Network and Security Management AI and Machine Learning for Network and Security Management covers a range of key topics of network automation for network and security management, including resource allocation and scheduling, network planning and routing, encrypted traffic classification, anomaly detection, and security operations. In addition, the authors introduce their large-scale intelligent network management and operation system and elaborate on how the aforementioned areas can be integrated into this system, plus how the network service can benefit. Sample ideas covered in this thought-provoking work include: How cognitive means, e.g., knowledge transfer, can help with network and security management How different advanced AI and machine learning techniques can be useful and helpful to facilitate network automation How the introduced techniques can be applied to many other related network and security management tasks Network engineers, content service providers, and cybersecurity service providers can use AI and Machine Learning for Network and Security Management to make better and more informed decisions in their areas of specialization. Students in a variety of related study programs will also derive value from the work by gaining a base understanding of historical foundational knowledge and seeing the key recent developments that have been made in the field.

Beyond the Algorithm
Beyond the Algorithm

Author: Omar Santos

Publisher: Addison-Wesley Professional

Published: 2024-01-30

Total Pages: 536

ISBN-13: 0138268398

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As artificial intelligence (AI) becomes more and more woven into our everyday lives—and underpins so much of the infrastructure we rely on—the ethical, security, and privacy implications require a critical approach that draws not simply on the programming and algorithmic foundations of the technology. Bringing together legal studies, philosophy, cybersecurity, and academic literature, Beyond the Algorithm examines these complex issues with a comprehensive, easy-to-understand analysis and overview. The book explores the ethical challenges that professionals—and, increasingly, users—are encountering as AI becomes not just a promise of the future, but a powerful tool of the present. An overview of the history and development of AI, from the earliest pioneers in machine learning to current applications and how it might shape the future Introduction to AI models and implementations, as well as examples of emerging AI trends Examination of vulnerabilities, including insight into potential real-world threats, and best practices for ensuring a safe AI deployment Discussion of how to balance accountability, privacy, and ethics with regulatory and legislative concerns with advancing AI technology A critical perspective on regulatory obligations, and repercussions, of AI with copyright protection, patent rights, and other intellectual property dilemmas An academic resource and guide for the evolving technical and intellectual challenges of AI Leading figures in the field bring to life the ethical issues associated with AI through in-depth analysis and case studies in this comprehensive examination.

Implications of Artificial Intelligence for Cybersecurity
Implications of Artificial Intelligence for Cybersecurity

Author: National Academies of Sciences, Engineering, and Medicine

Publisher: National Academies Press

Published: 2020-01-27

Total Pages: 99

ISBN-13: 0309494508

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In recent years, interest and progress in the area of artificial intelligence (AI) and machine learning (ML) have boomed, with new applications vigorously pursued across many sectors. At the same time, the computing and communications technologies on which we have come to rely present serious security concerns: cyberattacks have escalated in number, frequency, and impact, drawing increased attention to the vulnerabilities of cyber systems and the need to increase their security. In the face of this changing landscape, there is significant concern and interest among policymakers, security practitioners, technologists, researchers, and the public about the potential implications of AI and ML for cybersecurity. The National Academies of Sciences, Engineering, and Medicine convened a workshop on March 12-13, 2019 to discuss and explore these concerns. This publication summarizes the presentations and discussions from the workshop.

Machine Learning for Cyber Agents
Machine Learning for Cyber Agents

Author: Stanislav Abaimov

Publisher: Springer Nature

Published: 2022-01-27

Total Pages: 235

ISBN-13: 3030915859

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The cyber world has been both enhanced and endangered by AI. On the one hand, the performance of many existing security services has been improved, and new tools created. On the other, it entails new cyber threats both through evolved attacking capacities and through its own imperfections and vulnerabilities. Moreover, quantum computers are further pushing the boundaries of what is possible, by making machine learning cyber agents faster and smarter. With the abundance of often-confusing information and lack of trust in the diverse applications of AI-based technologies, it is essential to have a book that can explain, from a cyber security standpoint, why and at what stage the emerging, powerful technology of machine learning can and should be mistrusted, and how to benefit from it while avoiding potentially disastrous consequences. In addition, this book sheds light on another highly sensitive area – the application of machine learning for offensive purposes, an aspect that is widely misunderstood, under-represented in the academic literature and requires immediate expert attention.

Artificial Intelligence for Cybersecurity
Artificial Intelligence for Cybersecurity

Author: Mark Stamp

Publisher: Springer Nature

Published: 2022-07-15

Total Pages: 388

ISBN-13: 3030970876

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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.

Zero Trust Networks
Zero Trust Networks

Author: Evan Gilman

Publisher: "O'Reilly Media, Inc."

Published: 2017-06-19

Total Pages: 240

ISBN-13: 149196216X

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The perimeter defenses guarding your network perhaps are not as secure as you think. Hosts behind the firewall have no defenses of their own, so when a host in the "trusted" zone is breached, access to your data center is not far behind. That’s an all-too-familiar scenario today. With this practical book, you’ll learn the principles behind zero trust architecture, along with details necessary to implement it. The Zero Trust Model treats all hosts as if they’re internet-facing, and considers the entire network to be compromised and hostile. By taking this approach, you’ll focus on building strong authentication, authorization, and encryption throughout, while providing compartmentalized access and better operational agility. Understand how perimeter-based defenses have evolved to become the broken model we use today Explore two case studies of zero trust in production networks on the client side (Google) and on the server side (PagerDuty) Get example configuration for open source tools that you can use to build a zero trust network Learn how to migrate from a perimeter-based network to a zero trust network in production