Generative adversarial networks cybersecurity (17 resultados)

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  • Idioma: Inglés

    Editorial: Auerbach Publications, 2026

    1041098014 / 9781041098010

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    Editorial: Auerbach Publications, 2026

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    Editorial: Auerbach Publications, 2026

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    Librería: GreatBookPrices, Columbia, MD, Estados Unidos de AmericaGreatBookPrices

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    Editorial: Auerbach Publications, 2026

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    Librería: GreatBookPricesUK, Woodford Green, Reino UnidoGreatBookPricesUK

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  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, 2026

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    Librería: THE SAINT BOOKSTORE, Southport, Reino UnidoTHE SAINT BOOKSTORE

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    Editorial: CRC Press, 2026

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

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    Librería: Books Puddle, Woodside, NY, Estados Unidos de AmericaBooks Puddle

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    Editorial: CRC Press, 2026

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

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    Editorial: Auerbach Publications, 2026

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    Librería: Biblios, frankfurt am main, HESSE, AlemaniaBiblios

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  • Idioma: Inglés

    Editorial: CRC Press, 2026

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    Librería: moluna, Greven, Alemaniamoluna

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    Condición: New. Dr. E. Chandra Blessie is currently working as dean, Innovation, School of Innovation, KG College of Arts and Science, Coimbatore, Tamil Nadu, India. She has 23 years of teaching experience. She is guiding Ph.D. research scholars. She ha.

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    Editorial: Auerbach Pub, 2026

    1041098014 / 9781041098010

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    Librería: Revaluation Books, Exeter, Reino UnidoRevaluation Books

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    Hardcover. Condición: Brand New. 264 pages. 9.18x6.12x9.45 inches. In Stock.

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd (Sales) Mai 2026, 2026

    1041098014 / 9781041098010

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

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    Buch. Condición: Neu. Neuware - Generative Adversarial Networks (GANs) play a crucial dual role in cybersecurity, serving both as powerful defensive tools and sophisticated attack vectors that security professionals must understand and counter. GANs are invaluable for generating synthetic datasets to train cybersecurity models when real attack data is scarce or sensitive, creating realistic network traffic patterns for testing intrusion detection systems, and augmenting threat intelligence by simulating various attack scenarios without exposing actual vulnerabilities.Exploring the application of GAN models in intrusion detection, anomaly detection, and cybercrime, Generative Adversarial Networks for Cybersecurity: Protecting Data and Networks covers how GANs can be applied to pinpoint security holes, vulnerabilities, viruses, malware, phishing attacks, and other security risks. It explains how advanced GANs integrated with such digital technologies as the Internet of Things (IoT), cloud-native computing, edge analytics, serverless technology, and blockchain to protect and secure data and information from security breaches. The book also discusses how GANs can identify outliers, performance bottlenecks, and other issues in cloud infrastructure modules, applications, and data. Other topics featured in the book include: - GAN-based security's ethical and privacy concerns - GANs and explainable artificial intelligence (AI) - Building trustworthy sixth-generation (6G) networks with Generative Adversarial Learning (GAL) - Intrusion detection systems enhanced by GANs GANs are a valuable tool for enhancing cybersecurity efforts by generating synthetic data and images that can show unusual patterns in data. This book helps researchers, academics, and professionals realize the potential of this powerful tool by presenting the latest innovations and applications of GANs in cybersecurity.…

  • Idioma: Inglés

    Editorial: Taylor & Francis Ltd, London, 2026

    1041098014 / 9781041098010

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

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    EUR 103,06

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    Hardcover. Condición: new. Hardcover. Generative Adversarial Networks (GANs) play a crucial dual role in cybersecurity, serving both as powerful defensive tools and sophisticated attack vectors that security professionals must understand and counter. GANs are invaluable for generating synthetic datasets to train cybersecurity models when real attack data is scarce or sensitive, creating realistic network traffic patterns for testing intrusion detection systems, and augmenting threat intelligence by simulating various attack scenarios without exposing actual vulnerabilities.Exploring the application of GAN models in intrusion detection, anomaly detection, and cybercrime, Generative Adversarial Networks for Cybersecurity: Protecting Data and Networks covers how GANs can be applied to pinpoint security holes, vulnerabilities, viruses, malware, phishing attacks, and other security risks. It explains how advanced GANs integrated with such digital technologies as the Internet of Things (IoT), cloud-native computing, edge analytics, serverless technology, and blockchain to protect and secure data and information from security breaches. The book also discusses how GANs can identify outliers, performance bottlenecks, and other issues in cloud infrastructure modules, applications, and data. Other topics featured in the book include:GAN-based securitys ethical and privacy concernsGANs and explainable artificial intelligence (AI)Building trustworthy sixth-generation (6G) networks with Generative Adversarial Learning (GAL)Intrusion detection systems enhanced by GANsGANs are a valuable tool for enhancing cybersecurity efforts by generating synthetic data and images that can show unusual patterns in data. This book helps researchers, academics, and professionals realize the potential of this powerful tool by presenting the latest innovations and applications of GANs in cybersecurity. This book explores the application of diversified generative adversarial network (GAN) models in the fields of intrusion detection, anomaly detection, and cybercrime. It discusses how GANs can be smartly applied to pinpoint vulnerabilities and security attacks, as well as discusses ethical and privacy concerns. 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: Taylor & Francis Ltd, London, 2026

    1041098014 / 9781041098010

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    Librería: CitiRetail, Stevenage, Reino UnidoCitiRetail

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    Hardcover. Condición: new. Hardcover. Generative Adversarial Networks (GANs) play a crucial dual role in cybersecurity, serving both as powerful defensive tools and sophisticated attack vectors that security professionals must understand and counter. GANs are invaluable for generating synthetic datasets to train cybersecurity models when real attack data is scarce or sensitive, creating realistic network traffic patterns for testing intrusion detection systems, and augmenting threat intelligence by simulating various attack scenarios without exposing actual vulnerabilities.Exploring the application of GAN models in intrusion detection, anomaly detection, and cybercrime, Generative Adversarial Networks for Cybersecurity: Protecting Data and Networks covers how GANs can be applied to pinpoint security holes, vulnerabilities, viruses, malware, phishing attacks, and other security risks. It explains how advanced GANs integrated with such digital technologies as the Internet of Things (IoT), cloud-native computing, edge analytics, serverless technology, and blockchain to protect and secure data and information from security breaches. The book also discusses how GANs can identify outliers, performance bottlenecks, and other issues in cloud infrastructure modules, applications, and data. Other topics featured in the book include:GAN-based securitys ethical and privacy concernsGANs and explainable artificial intelligence (AI)Building trustworthy sixth-generation (6G) networks with Generative Adversarial Learning (GAL)Intrusion detection systems enhanced by GANsGANs are a valuable tool for enhancing cybersecurity efforts by generating synthetic data and images that can show unusual patterns in data. This book helps researchers, academics, and professionals realize the potential of this powerful tool by presenting the latest innovations and applications of GANs in cybersecurity. This book explores the application of diversified generative adversarial network (GAN) models in the fields of intrusion detection, anomaly detection, and cybercrime. It discusses how GANs can be smartly applied to pinpoint vulnerabilities and security attacks, as well as discusses ethical and privacy concerns. 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: Taylor & Francis Ltd, London, 2026

    1041098014 / 9781041098010

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    Librería: AussieBookSeller, Truganina, VIC, AustraliaAussieBookSeller

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    Hardcover. Condición: new. Hardcover. Generative Adversarial Networks (GANs) play a crucial dual role in cybersecurity, serving both as powerful defensive tools and sophisticated attack vectors that security professionals must understand and counter. GANs are invaluable for generating synthetic datasets to train cybersecurity models when real attack data is scarce or sensitive, creating realistic network traffic patterns for testing intrusion detection systems, and augmenting threat intelligence by simulating various attack scenarios without exposing actual vulnerabilities.Exploring the application of GAN models in intrusion detection, anomaly detection, and cybercrime, Generative Adversarial Networks for Cybersecurity: Protecting Data and Networks covers how GANs can be applied to pinpoint security holes, vulnerabilities, viruses, malware, phishing attacks, and other security risks. It explains how advanced GANs integrated with such digital technologies as the Internet of Things (IoT), cloud-native computing, edge analytics, serverless technology, and blockchain to protect and secure data and information from security breaches. The book also discusses how GANs can identify outliers, performance bottlenecks, and other issues in cloud infrastructure modules, applications, and data. Other topics featured in the book include:GAN-based securitys ethical and privacy concernsGANs and explainable artificial intelligence (AI)Building trustworthy sixth-generation (6G) networks with Generative Adversarial Learning (GAL)Intrusion detection systems enhanced by GANsGANs are a valuable tool for enhancing cybersecurity efforts by generating synthetic data and images that can show unusual patterns in data. This book helps researchers, academics, and professionals realize the potential of this powerful tool by presenting the latest innovations and applications of GANs in cybersecurity. This book explores the application of diversified generative adversarial network (GAN) models in the fields of intrusion detection, anomaly detection, and cybercrime. It discusses how GANs can be smartly applied to pinpoint vulnerabilities and security attacks, as well as discusses ethical and privacy concerns. 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.…