Challenges And Solutions For Cybersecurity And Adversarial Machine Learning
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Challenges And Solutions For Cybersecurity And Adversarial Machine Learning
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Author : Ul Rehman, Shafiq
language : en
Publisher: IGI Global
Release Date : 2025-06-06
Challenges And Solutions For Cybersecurity And Adversarial Machine Learning written by Ul Rehman, Shafiq and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-06-06 with Computers categories.
Adversarial machine learning poses a threat to cybersecurity by exploiting vulnerabilities in AI models through manipulated inputs. These attacks can cause systems in healthcare, finance, and autonomous vehicles to make dangerous or misleading decisions. A major challenge lies in detecting these small issues and defending learning models and organizational data without sacrificing performance. Ongoing research and cross-sector collaboration are essential to develop robust, ethical, and secure machine learning systems. Further research may reveal better solutions to converge cyber technology, security, and machine learning tools. Challenges and Solutions for Cybersecurity and Adversarial Machine Learning explores adversarial machine learning and deep learning within cybersecurity. It examines foundational knowledge, highlights vulnerabilities and threats, and proposes cutting-edge solutions to counteract adversarial attacks on AI systems. This book covers topics such as data privacy, federated learning, and threat detection, and is a useful resource for business owners, computer engineers, security professionals, academicians, researchers, and data scientists.
Adversarial Machine Learning
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Author : Aneesh Sreevallabh Chivukula
language : en
Publisher: Springer Nature
Release Date : 2023-03-06
Adversarial Machine Learning written by Aneesh Sreevallabh Chivukula and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2023-03-06 with Computers categories.
A critical challenge in deep learning is the vulnerability of deep learning networks to security attacks from intelligent cyber adversaries. Even innocuous perturbations to the training data can be used to manipulate the behaviour of deep networks in unintended ways. In this book, we review the latest developments in adversarial attack technologies in computer vision; natural language processing; and cybersecurity with regard to multidimensional, textual and image data, sequence data, and temporal data. In turn, we assess the robustness properties of deep learning networks to produce a taxonomy of adversarial examples that characterises the security of learning systems using game theoretical adversarial deep learning algorithms. The state-of-the-art in adversarial perturbation-based privacy protection mechanisms is also reviewed. We propose new adversary types for game theoretical objectives in non-stationary computational learning environments. Proper quantification of the hypothesis set in the decision problems of our research leads to various functional problems, oracular problems, sampling tasks, and optimization problems. We also address the defence mechanisms currently available for deep learning models deployed in real-world environments. The learning theories used in these defence mechanisms concern data representations, feature manipulations, misclassifications costs, sensitivity landscapes, distributional robustness, and complexity classes of the adversarial deep learning algorithms and their applications. In closing, we propose future research directions in adversarial deep learning applications for resilient learning system design and review formalized learning assumptions concerning the attack surfaces and robustness characteristics of artificial intelligence applications so as to deconstruct the contemporary adversarial deep learning designs. Given its scope, the book will be of interest to Adversarial Machine Learning practitioners and Adversarial Artificial Intelligence researchers whose work involves the design and application of Adversarial Deep Learning.
Exploiting Machine Learning For Robust Security
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Author : Minakshi
language : en
Publisher: IGI Global
Release Date : 2025-04-16
Exploiting Machine Learning For Robust Security written by Minakshi and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-04-16 with Computers categories.
In the digital world, ensuring robust security is critical as cyber threats become more sophisticated and pervasive. Machine learning can be used to strengthen cybersecurity and offer dynamic solutions that can identify, predict, and mitigate potential risks with unprecedented accuracy. By analyzing vast amounts of data, detecting patterns, and adapting to evolving threats, machine learning enables security systems to autonomously respond to anomalies and protect sensitive information in real-time. As technology advances, the integration of machine learning into security systems represents a critical step towards creating adaptive protection against the complex challenges of modern cybersecurity. Further research into the potential of machine learning in enhancing security protocols may highlight its ability to prevent cyberattacks, detect vulnerabilities, and ensure resilient defenses. Exploiting Machine Learning for Robust Security explores the world of machine learning, discussing the darknet of threat detection and vulnerability assessment, malware analysis, and predictive security analysis. Using case studies, it explores machine learning for threat detection and bolstered online defenses. This book covers topics such as anomaly detection, threat intelligence, and machine learning, and is a useful resource for engineers, security professionals, computer scientists, academicians, and researchers.
Ai Enhanced Cybersecurity For Industrial Automation
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Author : Pandey, Hari Mohan
language : en
Publisher: IGI Global
Release Date : 2025-05-09
Ai Enhanced Cybersecurity For Industrial Automation written by Pandey, Hari Mohan and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-05-09 with Computers categories.
As industrial automation systems become reliant on digital technologies, they face growing threats from sophisticated cyberattacks. Traditional cybersecurity measures often struggle to keep up with the evolving threat landscape, leaving critical infrastructure vulnerable. AI-enhanced cybersecurity offers a promising solution by leveraging machine learning and intelligent algorithms to detect, respond to, and even predict cyber threats in real time. By integrating AI into industrial cybersecurity frameworks, organizations can strengthen their defenses, ensure operational continuity, and protect valuable assets from malicious threats. AI-Enhanced Cybersecurity for Industrial Automation explores the integration of AI and cybersecurity in industry 5.0, emphasizing sustainability, resilience, and ethical considerations. It examines how industry 5.0 extends beyond automation and efficiency by incorporating human-centric, sustainable, and intelligent technologies into industrial ecosystems. This book covers topics such as blockchain, industrial engineering, and machine learning, and is a useful resource for computer engineers, business owners, security professionals, academicians, researchers, and scientists.
Game Theory And Machine Learning For Cyber Security
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Author : Charles A. Kamhoua
language : en
Publisher: John Wiley & Sons
Release Date : 2021-09-08
Game Theory And Machine Learning For Cyber Security written by Charles A. Kamhoua and has been published by John Wiley & Sons this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-09-08 with Technology & Engineering categories.
GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
Machine Intelligence Applications In Cyber Risk Management
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Author : Almaiah, Mohammed Amin
language : en
Publisher: IGI Global
Release Date : 2024-11-29
Machine Intelligence Applications In Cyber Risk Management written by Almaiah, Mohammed Amin and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-29 with Computers categories.
In an era where cyber threats are increasingly sophisticated and persistent, the intersection of machine intelligence and cyber-risk management represents a pivotal frontier in the defense against malicious actors. The rapid advancements of artificial intelligence (AI) and machine learning (ML) technologies offer unprecedented capabilities for identifying, analyzing, and mitigating cyber risks. These technologies not only improve the speed and accuracy of identifying potential threats but also enable proactive and adaptive security measures. Machine Intelligence Applications in Cyber-Risk Management explores the diverse applications of machine intelligence in cyber-risk management, providing a comprehensive overview of how AI and ML algorithms are utilized for automated incident response, threat intelligence gathering, and dynamic security postures. It addresses the pressing need for innovative solutions to combat cyber threats and offer insights into the future of cybersecurity, where machine intelligence plays a crucial role in creating resilient and adaptive defense mechanisms. Covering topics such as anomy detection algorithms, malware detection, and wireless sensor networks (WSNs), this book is an excellent resource for cybersecurity professionals, researchers, academicians, security analysts, threat intelligence experts, IT managers, and more.
Artificial Intelligence And Machine Learning For Enhancing Resilience Concepts Applications And Future Directions
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Author :
language : en
Publisher: Deep Science Publishing
Release Date : 2025-07-01
Artificial Intelligence And Machine Learning For Enhancing Resilience Concepts Applications And Future Directions written by and has been published by Deep Science Publishing this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-07-01 with Computers categories.
As contemporary societies face unprecedented challenges such as mounting mental health issues, environmental crises, and socioeconomic insecurity, the urgency of developing objective, scalable, and dynamic methodologies to study resilience has never been greater. This book arises at the intersection of cutting-edge technology and human insight. It focuses on the possibility for AI and ML to transform resilience assessment, prediction, and interventions across the individual, organizational, and ecological levels. The chapters included in this book represent an organized synthesis of cutting-edge science, pragmatic applications, and prospective potential. With machine learning algorithms to estimate psychological resilience and AI-based models for climate change adaptation and ecosystem management, this book demonstrates the rich innovations that are emerging at the cross-sector of technology and resilience science. Perhaps most importantly, this book does not gloss over the urgent ethical, technical, and regulatory issues that arise when AI is introduced to sensitive topics such as mental health and environmental management. Questions about data privacy, algorithmic bias, model interpretability, and equitable technology deployment are thoroughly investigated, providing lessons learned and suggestions for moving ahead. A significant strength of this work is its global focus. Showcasing work from contributors of various methodologies and regions provides the latest views on new methodologies, strategies for practical implementation, and on what still needs to be invented. This guarantees that the publication engages with the messy socio-cultural and environmental contexts in which these interventions work and that it doesn’t just mirror technological possibilities. For academicians, practitioners, technologists, and policymakers, this book is both a fundamental reference and an outlook resource. It provides: Holistic examination of AI and ML in the context of psychological, organizational, and ecological resilience. In-depth reviews on methodological innovations, such as deep learning, natural language processing, and sensor-based assessments. Unprecedented appraisals of barriers to implementation, with ethical and regulatory considerations. We trust that this book will inspire conversation, fuel innovation, and support a future in which technology supplements, rather than replaces, human ability to adapt, recover, and flourish. We encourage readers to critique the content, to reflect on how AI, ML, and resilience intersect in their particular contexts, and to join us in shaping a future where technological and human resilience evolve together.
Leveraging Artificial Intelligence Ai Competencies For Next Generation Cybersecurity Solutions
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Author : Pethuru Raj
language : en
Publisher: CRC Press
Release Date : 2024-11-22
Leveraging Artificial Intelligence Ai Competencies For Next Generation Cybersecurity Solutions written by Pethuru Raj and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-11-22 with Computers categories.
Modern enterprises are facing growing cybersecurity issues due to the massive volume of security-related data they generate over time. AI systems can be developed to resolve a range of these issues with comparative ease. This new book describes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help eliminate them. With chapters from industry and security experts, this volume discribes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help elimintate them. With chapters from industry and security experts, this volume discusses the many new and emerging AI technologies and approaches that can be harnessed to combat cyberattacks, including big data analytics techniques, deep neural networks, cloud computer networks, convolutional neural networks, IoT edge devices, machine learning approaches, deep learning, blockchain technology, convolutional neural networks, and more. Some unique features of this book include: Detailed overview of various security analytics techniques and tools Comprehensive descriptions of the emerging and evolving aspects of artificial intelligence (AI) technologies Industry case studies for practical comprehension and application This book, Leveraging the Artificial Intelligence Competencies for Next-Generation Cybersecurity Solutions, illustrates how AI is a futuristic and flexible technology that can be effectively used for tackling the growing menace of cybercriminals. It clearly demystifies the unique contributions of AI algorithms, models, frameworks, and libraries in nullifying the cyberattacks. The volume will be a valuable resource for research students, scholars, academic professors, business executives, security architects, and consultants in the IT industry.
Handbook Of Research On Cybersecurity Issues And Challenges For Business And Fintech Applications
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Author : Saeed, Saqib
language : en
Publisher: IGI Global
Release Date : 2022-10-21
Handbook Of Research On Cybersecurity Issues And Challenges For Business And Fintech Applications written by Saeed, Saqib and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-10-21 with Computers categories.
Digital transformation in organizations optimizes the business processes but also brings additional challenges in the form of security threats and vulnerabilities. Cyberattacks incur financial losses for organizations and can affect their reputations. Due to this, cybersecurity has become critical for business enterprises. Extensive technological adoption in businesses and the evolution of FinTech applications require reasonable cybersecurity measures to protect organizations from internal and external security threats. Recent advances in the cybersecurity domain such as zero trust architecture, application of machine learning, and quantum and post-quantum cryptography have colossal potential to secure technological infrastructures. The Handbook of Research on Cybersecurity Issues and Challenges for Business and FinTech Applications discusses theoretical foundations and empirical studies of cybersecurity implications in global digital transformation and considers cybersecurity challenges in diverse business areas. Covering essential topics such as artificial intelligence, social commerce, and data leakage, this reference work is ideal for cybersecurity professionals, business owners, managers, policymakers, researchers, scholars, academicians, practitioners, instructors, and students.
Utilizing Generative Ai For Cyber Defense Strategies
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Author : Jhanjhi, Noor Zaman
language : en
Publisher: IGI Global
Release Date : 2024-09-12
Utilizing Generative Ai For Cyber Defense Strategies written by Jhanjhi, Noor Zaman and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-09-12 with Computers categories.
As cyber threats become increasingly sophisticated, the need for innovative defense strategies becomes urgent. Generative artificial intelligence (AI) offers a revolutionary approach to enhance cybersecurity. By utilizing advanced algorithms, data analysis, and machine learning, generative AI can simulate complex attack scenarios, identify vulnerabilities, and develop proactive defense mechanisms while adapting to modern-day cyber-attacks. AI strengthens current organizational security while offering quick, effective responses to emerging threats. Decisive strategies are needed to integrate generative AI into businesses defense strategies and protect organizations from attacks, secure digital data, and ensure safe business processes. Utilizing Generative AI for Cyber Defense Strategies explores the utilization of generative AI tools in organizational cyber security and defense. Strategies for effective threat detection and mitigation are presented, with an emphasis on deep learning, artificial intelligence, and Internet of Things (IoT) technology. This book covers topics such as cyber security, threat intelligence, and behavior analysis, and is a useful resource for computer engineers, security professionals, business owners, government officials, data analysts, academicians, scientists, and researchers.