Isbn: 9789999343725 - hands-on ai system security: attacks on ml models & cyber defense (8 resultados)

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  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: California Books, Miami, FL, Estados Unidos de AmericaCalifornia Books

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    EUR 49,73

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  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: PBShop.store UK, Fairford, GLOS, Reino UnidoPBShop.store UK

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    PAP. Condición: New. New Book. Shipped from UK. Established seller since 2000.

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    EUR 61,53

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    Paperback. Condición: Brand New. 67 pages. 6.00x0.16x9.00 inches. In Stock.

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: Grand Eagle Retail, Bensenville, IL, Estados Unidos de AmericaGrand Eagle Retail

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    EUR 49,72

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    Paperback. Condición: new. Paperback. Artificial Intelligence is transforming modern technology, from healthcare and finance to autonomous systems and cybersecurity. However, as AI systems become more powerful and widely deployed, they are also becoming prime targets for sophisticated cyberattacks. Machine learning models can be manipulated, poisoned, stolen, or deceived-creating serious security and privacy risks for organizations worldwide. Hands-On AI System Security: Attacks on ML Models & Cyber Defense provides a practical and research-driven exploration of the rapidly evolving field of AI security. This book guides readers through real-world attacks against machine learning systems, including adversarial attacks, data poisoning, model evasion, prompt injection, model inversion, model extraction, deepfake manipulation, and AI-driven cyber threats. Alongside attack methodologies, it presents effective defense mechanisms, secure AI development practices, threat detection strategies, explainable AI security techniques, and modern cyber defense frameworks. The book offers detailed coverage of secure machine learning pipelines, AI risk assessment, adversarial training, federated learning security, cloud AI protection, and AI governance principles. Readers will explore how attackers exploit vulnerabilities in neural networks, large language models (LLMs), computer vision systems, and intelligent automation platforms, while also learning practical strategies to mitigate these threats using defensive AI techniques and security monitoring frameworks. Key topics covered in this book include: Fundamentals of AI and Machine Learning Security Adversarial Machine Learning Attacks Data Poisoning and Model Manipulation Prompt Injection and LLM Security AI Malware and Automated Cyber Threats Secure AI Model Deployment and Monitoring This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability. …

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: AHA-BUCH GmbH, Einbeck, AlemaniaAHA-BUCH GmbH

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    Condición: Nuevo

    EUR 64,77

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    Cantidad disponible: 2 disponibles

    Taschenbuch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Artificial Intelligence is transforming modern technology, from healthcare and finance to autonomous systems and cybersecurity. However, as AI systems become more powerful and widely deployed, they are also becoming prime targets for sophisticated cyberattacks. Machine learning models can be manipulated, poisoned, stolen, or deceived-creating serious security and privacy risks for organizations worldwide. Hands-On AI System Security: Attacks on ML Models & Cyber Defense provides a practical and research-driven exploration of the rapidly evolving field of AI security. This book guides readers through real-world attacks against machine learning systems, including adversarial attacks, data poisoning, model evasion, prompt injection, model inversion, model extraction, deepfake manipulation, and AI-driven cyber threats. Alongside attack methodologies, it presents effective defense mechanisms, secure AI development practices, threat detection strategies, explainable AI security techniques, and modern cyber defense frameworks. The book offers detailed coverage of secure machine learning pipelines, AI risk assessment, adversarial training, federated learning security, cloud AI protection, and AI governance principles. Readers will explore how attackers exploit vulnerabilities in neural networks, large language models (LLMs), computer vision systems, and intelligent automation platforms, while also learning practical strategies to mitigate these threats using defensive AI techniques and security monitoring frameworks. Key topics covered in this book include: Fundamentals of AI and Machine Learning Security Adversarial Machine Learning Attacks Data Poisoning and Model Manipulation Prompt Injection and LLM Security AI Malware and Automated Cyber Threats Secure AI Model Deployment and Monitoring.…

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    EUR 75,79

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    Cantidad disponible: 1 disponibles

    Paperback. Condición: new. Paperback. Artificial Intelligence is transforming modern technology, from healthcare and finance to autonomous systems and cybersecurity. However, as AI systems become more powerful and widely deployed, they are also becoming prime targets for sophisticated cyberattacks. Machine learning models can be manipulated, poisoned, stolen, or deceived-creating serious security and privacy risks for organizations worldwide. Hands-On AI System Security: Attacks on ML Models & Cyber Defense provides a practical and research-driven exploration of the rapidly evolving field of AI security. This book guides readers through real-world attacks against machine learning systems, including adversarial attacks, data poisoning, model evasion, prompt injection, model inversion, model extraction, deepfake manipulation, and AI-driven cyber threats. Alongside attack methodologies, it presents effective defense mechanisms, secure AI development practices, threat detection strategies, explainable AI security techniques, and modern cyber defense frameworks. The book offers detailed coverage of secure machine learning pipelines, AI risk assessment, adversarial training, federated learning security, cloud AI protection, and AI governance principles. Readers will explore how attackers exploit vulnerabilities in neural networks, large language models (LLMs), computer vision systems, and intelligent automation platforms, while also learning practical strategies to mitigate these threats using defensive AI techniques and security monitoring frameworks. Key topics covered in this book include: Fundamentals of AI and Machine Learning Security Adversarial Machine Learning Attacks Data Poisoning and Model Manipulation Prompt Injection and LLM Security AI Malware and Automated Cyber Threats Secure AI Model Deployment and Monitoring 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. …

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    EUR 64,66

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    Cantidad disponible: 1 disponibles

    Paperback. Condición: new. Paperback. Artificial Intelligence is transforming modern technology, from healthcare and finance to autonomous systems and cybersecurity. However, as AI systems become more powerful and widely deployed, they are also becoming prime targets for sophisticated cyberattacks. Machine learning models can be manipulated, poisoned, stolen, or deceived-creating serious security and privacy risks for organizations worldwide. Hands-On AI System Security: Attacks on ML Models & Cyber Defense provides a practical and research-driven exploration of the rapidly evolving field of AI security. This book guides readers through real-world attacks against machine learning systems, including adversarial attacks, data poisoning, model evasion, prompt injection, model inversion, model extraction, deepfake manipulation, and AI-driven cyber threats. Alongside attack methodologies, it presents effective defense mechanisms, secure AI development practices, threat detection strategies, explainable AI security techniques, and modern cyber defense frameworks. The book offers detailed coverage of secure machine learning pipelines, AI risk assessment, adversarial training, federated learning security, cloud AI protection, and AI governance principles. Readers will explore how attackers exploit vulnerabilities in neural networks, large language models (LLMs), computer vision systems, and intelligent automation platforms, while also learning practical strategies to mitigate these threats using defensive AI techniques and security monitoring frameworks. Key topics covered in this book include: Fundamentals of AI and Machine Learning Security Adversarial Machine Learning Attacks Data Poisoning and Model Manipulation Prompt Injection and LLM Security AI Malware and Automated Cyber Threats Secure AI Model Deployment and Monitoring This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. …

  • Idioma: Inglés

    Editorial: Eliva Press, 2026

    9999343724 / 9789999343725

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    Librería: preigu, Osnabrück, Alemaniapreigu

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    Condición: Nuevo

    EUR 54,35

    Envío por EUR 70,00 
    Se envía de Alemania a Estados Unidos de America

    Cantidad disponible: 5 disponibles

    Taschenbuch. Condición: Neu. Hands-On AI System Security | Attacks on ML Models & Cyber Defense | Md Ghufran Alam (u. a.) | Taschenbuch | Englisch | 2026 | Eliva Press | EAN 9789999343725 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…