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Librería: GreatBookPrices, Columbia, MD, Estados Unidos de America
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Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2025
ISBN 10: 1041051352 ISBN 13: 9781041051350
Librería: Rarewaves.com USA, London, LONDO, Reino Unido
EUR 68,08
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Añadir al carritoPaperback. Condición: New. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. As IoT devices proliferate in both consumer and industrial settings, their inherent vulnerabilities-such as weak authentication, limited processing power, and lack of regular updates-make them prime targets for attackers. The book begins by exploring how IoT botnets are formed, highlighting key attack vectors such as malware propagation, command, and control (CandC) mechanisms, and commonly exploited protocols such as Telnet and UPnP. Notable case studies, including the Mirai and Mozi botnets, illustrate real-world impacts, emphasizing the scale and damage these threats can inflict. The core of the book then transitions into detection methodologies, covering both traditional and AI-driven approaches. Techniques such as signature-based detection, anomaly detection using machine learning, network traffic analysis, and honeypot deployment are thoroughly examined. The authors also address the challenges in detecting IoT botnets, including encrypted traffic, device heterogeneity, and low visibility in resource-constrained devices. Furthermore, the book emphasizes the importance of proactive defense strategies, such as firmware hardening, secure boot mechanisms, and real-time behavioral analytics. It underscores the role of collaborative intelligence sharing among stakeholders to enhance detection capabilities. By integrating theoretical concepts with practical insights and current research trends, the book provides a comprehensive guide for researchers, cybersecurity professionals, and IoT developers aiming to understand and counteract botnet threats. Ultimately, Anatomy of IoT Botnet and Detection Methods serves as a crucial resource for strengthening the cybersecurity posture of IoT ecosystems through informed detection and mitigation practices. The content of the book is categorized into the following sub-sections: Introduction to IoT and Botnets: An overview of IoT technology, its adoption, and the rising threat of botnets. IoT Device Vulnerabilities: Analysis of common security weaknesses in IoT devices that cybercriminals exploit. Botnet Architecture: Detailed examination of how IoT botnets are structured, including command-and-control mechanisms. Infection and Propagation: Methods used by attackers to spread malware across IoT networks. Detection Techniques: Overview of current detection methods, including anomaly detection, signature-based approaches, and machine learning. Mitigation Strategies: Practical advice on how to secure IoT devices, including best practices for manufacturers and users. Case Studies: Real-world examples of IoT botnet attacks and their impact.The book concludes with a discussion on the future of IoT security, emphasizing the need for continuous innovation in detection and preventi.
Librería: California Books, Miami, FL, Estados Unidos de America
EUR 68,12
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Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2025
ISBN 10: 1041051352 ISBN 13: 9781041051350
Librería: Rarewaves USA, OSWEGO, IL, Estados Unidos de America
EUR 72,54
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Añadir al carritoPaperback. Condición: New. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. As IoT devices proliferate in both consumer and industrial settings, their inherent vulnerabilities-such as weak authentication, limited processing power, and lack of regular updates-make them prime targets for attackers. The book begins by exploring how IoT botnets are formed, highlighting key attack vectors such as malware propagation, command, and control (CandC) mechanisms, and commonly exploited protocols such as Telnet and UPnP. Notable case studies, including the Mirai and Mozi botnets, illustrate real-world impacts, emphasizing the scale and damage these threats can inflict. The core of the book then transitions into detection methodologies, covering both traditional and AI-driven approaches. Techniques such as signature-based detection, anomaly detection using machine learning, network traffic analysis, and honeypot deployment are thoroughly examined. The authors also address the challenges in detecting IoT botnets, including encrypted traffic, device heterogeneity, and low visibility in resource-constrained devices. Furthermore, the book emphasizes the importance of proactive defense strategies, such as firmware hardening, secure boot mechanisms, and real-time behavioral analytics. It underscores the role of collaborative intelligence sharing among stakeholders to enhance detection capabilities. By integrating theoretical concepts with practical insights and current research trends, the book provides a comprehensive guide for researchers, cybersecurity professionals, and IoT developers aiming to understand and counteract botnet threats. Ultimately, Anatomy of IoT Botnet and Detection Methods serves as a crucial resource for strengthening the cybersecurity posture of IoT ecosystems through informed detection and mitigation practices. The content of the book is categorized into the following sub-sections: Introduction to IoT and Botnets: An overview of IoT technology, its adoption, and the rising threat of botnets. IoT Device Vulnerabilities: Analysis of common security weaknesses in IoT devices that cybercriminals exploit. Botnet Architecture: Detailed examination of how IoT botnets are structured, including command-and-control mechanisms. Infection and Propagation: Methods used by attackers to spread malware across IoT networks. Detection Techniques: Overview of current detection methods, including anomaly detection, signature-based approaches, and machine learning. Mitigation Strategies: Practical advice on how to secure IoT devices, including best practices for manufacturers and users. Case Studies: Real-world examples of IoT botnet attacks and their impact.The book concludes with a discussion on the future of IoT security, emphasizing the need for continuous innovation in detection and preventi.
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Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2025
ISBN 10: 1041051352 ISBN 13: 9781041051350
Librería: Rarewaves USA United, OSWEGO, IL, Estados Unidos de America
EUR 74,67
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Añadir al carritoPaperback. Condición: New. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. As IoT devices proliferate in both consumer and industrial settings, their inherent vulnerabilities-such as weak authentication, limited processing power, and lack of regular updates-make them prime targets for attackers. The book begins by exploring how IoT botnets are formed, highlighting key attack vectors such as malware propagation, command, and control (CandC) mechanisms, and commonly exploited protocols such as Telnet and UPnP. Notable case studies, including the Mirai and Mozi botnets, illustrate real-world impacts, emphasizing the scale and damage these threats can inflict. The core of the book then transitions into detection methodologies, covering both traditional and AI-driven approaches. Techniques such as signature-based detection, anomaly detection using machine learning, network traffic analysis, and honeypot deployment are thoroughly examined. The authors also address the challenges in detecting IoT botnets, including encrypted traffic, device heterogeneity, and low visibility in resource-constrained devices. Furthermore, the book emphasizes the importance of proactive defense strategies, such as firmware hardening, secure boot mechanisms, and real-time behavioral analytics. It underscores the role of collaborative intelligence sharing among stakeholders to enhance detection capabilities. By integrating theoretical concepts with practical insights and current research trends, the book provides a comprehensive guide for researchers, cybersecurity professionals, and IoT developers aiming to understand and counteract botnet threats. Ultimately, Anatomy of IoT Botnet and Detection Methods serves as a crucial resource for strengthening the cybersecurity posture of IoT ecosystems through informed detection and mitigation practices. The content of the book is categorized into the following sub-sections: Introduction to IoT and Botnets: An overview of IoT technology, its adoption, and the rising threat of botnets. IoT Device Vulnerabilities: Analysis of common security weaknesses in IoT devices that cybercriminals exploit. Botnet Architecture: Detailed examination of how IoT botnets are structured, including command-and-control mechanisms. Infection and Propagation: Methods used by attackers to spread malware across IoT networks. Detection Techniques: Overview of current detection methods, including anomaly detection, signature-based approaches, and machine learning. Mitigation Strategies: Practical advice on how to secure IoT devices, including best practices for manufacturers and users. Case Studies: Real-world examples of IoT botnet attacks and their impact.The book concludes with a discussion on the future of IoT security, emphasizing the need for continuous innovation in detection and preventi.
Idioma: Inglés
Publicado por Taylor and Francis Ltd, GB, 2025
ISBN 10: 1041051352 ISBN 13: 9781041051350
Librería: Rarewaves.com UK, London, Reino Unido
EUR 63,44
Cantidad disponible: 2 disponibles
Añadir al carritoPaperback. Condición: New. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. As IoT devices proliferate in both consumer and industrial settings, their inherent vulnerabilities-such as weak authentication, limited processing power, and lack of regular updates-make them prime targets for attackers. The book begins by exploring how IoT botnets are formed, highlighting key attack vectors such as malware propagation, command, and control (CandC) mechanisms, and commonly exploited protocols such as Telnet and UPnP. Notable case studies, including the Mirai and Mozi botnets, illustrate real-world impacts, emphasizing the scale and damage these threats can inflict. The core of the book then transitions into detection methodologies, covering both traditional and AI-driven approaches. Techniques such as signature-based detection, anomaly detection using machine learning, network traffic analysis, and honeypot deployment are thoroughly examined. The authors also address the challenges in detecting IoT botnets, including encrypted traffic, device heterogeneity, and low visibility in resource-constrained devices. Furthermore, the book emphasizes the importance of proactive defense strategies, such as firmware hardening, secure boot mechanisms, and real-time behavioral analytics. It underscores the role of collaborative intelligence sharing among stakeholders to enhance detection capabilities. By integrating theoretical concepts with practical insights and current research trends, the book provides a comprehensive guide for researchers, cybersecurity professionals, and IoT developers aiming to understand and counteract botnet threats. Ultimately, Anatomy of IoT Botnet and Detection Methods serves as a crucial resource for strengthening the cybersecurity posture of IoT ecosystems through informed detection and mitigation practices. The content of the book is categorized into the following sub-sections: Introduction to IoT and Botnets: An overview of IoT technology, its adoption, and the rising threat of botnets. IoT Device Vulnerabilities: Analysis of common security weaknesses in IoT devices that cybercriminals exploit. Botnet Architecture: Detailed examination of how IoT botnets are structured, including command-and-control mechanisms. Infection and Propagation: Methods used by attackers to spread malware across IoT networks. Detection Techniques: Overview of current detection methods, including anomaly detection, signature-based approaches, and machine learning. Mitigation Strategies: Practical advice on how to secure IoT devices, including best practices for manufacturers and users. Case Studies: Real-world examples of IoT botnet attacks and their impact.The book concludes with a discussion on the future of IoT security, emphasizing the need for continuous innovation in detection and preventi.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2025
ISBN 10: 1041051352 ISBN 13: 9781041051350
Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de America
EUR 58,34
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. Paperback. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. As IoT devices proliferate in both consumer and industrial settings, their inherent vulnerabilitiessuch as weak authentication, limited processing power, and lack of regular updatesmake them prime targets for attackers. The book begins by exploring how IoT botnets are formed, highlighting key attack vectors such as malware propagation, command, and control (C&C) mechanisms, and commonly exploited protocols such as Telnet and UPnP. Notable case studies, including the Mirai and Mozi botnets, illustrate real-world impacts, emphasizing the scale and damage these threats can inflict. The core of the book then transitions into detection methodologies, covering both traditional and AI-driven approaches. Techniques such as signature-based detection, anomaly detection using machine learning, network traffic analysis, and honeypot deployment are thoroughly examined. The authors also address the challenges in detecting IoT botnets, including encrypted traffic, device heterogeneity, and low visibility in resource-constrained devices. Furthermore, the book emphasizes the importance of proactive defense strategies, such as firmware hardening, secure boot mechanisms, and real-time behavioral analytics. It underscores the role of collaborative intelligence sharing among stakeholders to enhance detection capabilities. By integrating theoretical concepts with practical insights and current research trends, the book provides a comprehensive guide for researchers, cybersecurity professionals, and IoT developers aiming to understand and counteract botnet threats. Ultimately, Anatomy of IoT Botnet and Detection Methods serves as a crucial resource for strengthening the cybersecurity posture of IoT ecosystems through informed detection and mitigation practices. The content of the book is categorized into the following sub-sections: Introduction to IoT and Botnets: An overview of IoT technology, its adoption, and the rising threat of botnets. IoT Device Vulnerabilities: Analysis of common security weaknesses in IoT devices that cybercriminals exploit. Botnet Architecture: Detailed examination of how IoT botnets are structured, including command-and-control mechanisms. Infection and Propagation: Methods used by attackers to spread malware across IoT networks. Detection Techniques: Overview of current detection methods, including anomaly detection, signature-based approaches, and machine learning. Mitigation Strategies: Practical advice on how to secure IoT devices, including best practices for manufacturers and users. Case Studies: Real-world examples of IoT botnet attacks and their impact.The book concludes with a discussion on the future of IoT security, emphasizing the need for continuous innovation in detection and prevention methods. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.
Librería: Revaluation Books, Exeter, Reino Unido
EUR 71,21
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Añadir al carritoPaperback. Condición: Brand New. 280 pages. 9.18x6.12x9.21 inches. In Stock. This item is printed on demand.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2025
ISBN 10: 1041051352 ISBN 13: 9781041051350
Librería: CitiRetail, Stevenage, Reino Unido
EUR 57,15
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. Paperback. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. As IoT devices proliferate in both consumer and industrial settings, their inherent vulnerabilitiessuch as weak authentication, limited processing power, and lack of regular updatesmake them prime targets for attackers. The book begins by exploring how IoT botnets are formed, highlighting key attack vectors such as malware propagation, command, and control (C&C) mechanisms, and commonly exploited protocols such as Telnet and UPnP. Notable case studies, including the Mirai and Mozi botnets, illustrate real-world impacts, emphasizing the scale and damage these threats can inflict. The core of the book then transitions into detection methodologies, covering both traditional and AI-driven approaches. Techniques such as signature-based detection, anomaly detection using machine learning, network traffic analysis, and honeypot deployment are thoroughly examined. The authors also address the challenges in detecting IoT botnets, including encrypted traffic, device heterogeneity, and low visibility in resource-constrained devices. Furthermore, the book emphasizes the importance of proactive defense strategies, such as firmware hardening, secure boot mechanisms, and real-time behavioral analytics. It underscores the role of collaborative intelligence sharing among stakeholders to enhance detection capabilities. By integrating theoretical concepts with practical insights and current research trends, the book provides a comprehensive guide for researchers, cybersecurity professionals, and IoT developers aiming to understand and counteract botnet threats. Ultimately, Anatomy of IoT Botnet and Detection Methods serves as a crucial resource for strengthening the cybersecurity posture of IoT ecosystems through informed detection and mitigation practices. The content of the book is categorized into the following sub-sections: Introduction to IoT and Botnets: An overview of IoT technology, its adoption, and the rising threat of botnets. IoT Device Vulnerabilities: Analysis of common security weaknesses in IoT devices that cybercriminals exploit. Botnet Architecture: Detailed examination of how IoT botnets are structured, including command-and-control mechanisms. Infection and Propagation: Methods used by attackers to spread malware across IoT networks. Detection Techniques: Overview of current detection methods, including anomaly detection, signature-based approaches, and machine learning. Mitigation Strategies: Practical advice on how to secure IoT devices, including best practices for manufacturers and users. Case Studies: Real-world examples of IoT botnet attacks and their impact.The book concludes with a discussion on the future of IoT security, emphasizing the need for continuous innovation in detection and prevention methods. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.
Librería: AHA-BUCH GmbH, Einbeck, Alemania
EUR 67,38
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Añadir al carritoTaschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets.
Idioma: Inglés
Publicado por Taylor & Francis Ltd, London, 2025
ISBN 10: 1041051352 ISBN 13: 9781041051350
Librería: AussieBookSeller, Truganina, VIC, Australia
EUR 109,84
Cantidad disponible: 1 disponibles
Añadir al carritoPaperback. Condición: new. Paperback. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. As IoT devices proliferate in both consumer and industrial settings, their inherent vulnerabilitiessuch as weak authentication, limited processing power, and lack of regular updatesmake them prime targets for attackers. The book begins by exploring how IoT botnets are formed, highlighting key attack vectors such as malware propagation, command, and control (C&C) mechanisms, and commonly exploited protocols such as Telnet and UPnP. Notable case studies, including the Mirai and Mozi botnets, illustrate real-world impacts, emphasizing the scale and damage these threats can inflict. The core of the book then transitions into detection methodologies, covering both traditional and AI-driven approaches. Techniques such as signature-based detection, anomaly detection using machine learning, network traffic analysis, and honeypot deployment are thoroughly examined. The authors also address the challenges in detecting IoT botnets, including encrypted traffic, device heterogeneity, and low visibility in resource-constrained devices. Furthermore, the book emphasizes the importance of proactive defense strategies, such as firmware hardening, secure boot mechanisms, and real-time behavioral analytics. It underscores the role of collaborative intelligence sharing among stakeholders to enhance detection capabilities. By integrating theoretical concepts with practical insights and current research trends, the book provides a comprehensive guide for researchers, cybersecurity professionals, and IoT developers aiming to understand and counteract botnet threats. Ultimately, Anatomy of IoT Botnet and Detection Methods serves as a crucial resource for strengthening the cybersecurity posture of IoT ecosystems through informed detection and mitigation practices. The content of the book is categorized into the following sub-sections: Introduction to IoT and Botnets: An overview of IoT technology, its adoption, and the rising threat of botnets. IoT Device Vulnerabilities: Analysis of common security weaknesses in IoT devices that cybercriminals exploit. Botnet Architecture: Detailed examination of how IoT botnets are structured, including command-and-control mechanisms. Infection and Propagation: Methods used by attackers to spread malware across IoT networks. Detection Techniques: Overview of current detection methods, including anomaly detection, signature-based approaches, and machine learning. Mitigation Strategies: Practical advice on how to secure IoT devices, including best practices for manufacturers and users. Case Studies: Real-world examples of IoT botnet attacks and their impact.The book concludes with a discussion on the future of IoT security, emphasizing the need for continuous innovation in detection and prevention methods. The book Anatomy of IoT Botnets and Detection Methods delves into the evolving landscape of cybersecurity threats associated with the Internet of Things (IoT), specifically focusing on the anatomy, behavior, and detection of IoT-based botnets. This item is printed on demand. Shipping may be from our Sydney, NSW warehouse or from our UK or US warehouse, depending on stock availability.