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Generative Cybersecurity by Sikos Leslie (17 results)

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  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer 11/16/2025, 2025

    3032052491 / 9783032052490

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    Paperback or Softback. Condition: New. Generative AI in Cybersecurity. Book.

  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer-Nature New York Inc, 2025

    3032052491 / 9783032052490

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    Paperback. Condition: Brand New. 65 pages. 9.25x6.10x9.21 inches. In Stock.

  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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    Taschenbuch. Condition: Neu. Druck auf Anfrage Neuware - Printed after ordering - This book explores the most common generative AI (GenAI) tools and techniques used by malicious actors for hacking and cyber-deception, along with the security risks of large language models (LLMs). It also covers how LLM deployment and use can be secured, and how generative AI can be utilized in SOC automation.The rapid advancements and growing variety of publicly available generative AI tools enables cybersecurity use cases for threat modeling, security awareness support, web application scanning, actionable insights, and alert fatigue prevention. However, they also came with a steep rise in the number of offensive/rogue/malicious generative AI applications. With large language models, social engineering tactics can reach new heights in the efficiency of phishing campaigns and cyber-deception via synthetic media generation (misleading deepfake images and videos, faceswapping, morphs, and voice clones). The result is a new era of cybersecurity that necessitates innovative approaches to detect and mitigate sophisticated cyberattacks, and to prevent hyper-realistic cyber-deception.This work provides a starting point for researchers and students diving into malicious chatbot use, system administrators trying to harden the security of GenAI deployments, and organizations prone to sensitive data leak through shadow AI. It also benefits SOC analysts considering generative AI for partially automating incident detection and response, and GenAI vendors working on security guardrails against malicious prompting.…

  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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    Taschenbuch. Condition: Neu. Generative AI in Cybersecurity | Leslie F. Sikos | Taschenbuch | SpringerBriefs in Cybersecurity | x | Englisch | 2025 | Springer | EAN 9783032052490 | Verantwortliche Person für die EU: Springer Verlag GmbH, Tiergartenstr. 17, 69121 Heidelberg, juergen[dot]hartmann[at]springer[dot]com | Anbieter: preigu. …

  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer-Verlag Gmbh Nov 2025, 2025

    3032052491 / 9783032052490

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    Taschenbuch. Condition: Neu. This item is printed on demand - it takes 3-4 days longer - Neuware -This book explores the most common generative AI (GenAI) tools and techniques used by malicious actors for hacking and cyber-deception, along with the security risks of large language models (LLMs). It also covers how LLM deployment and use can be secured, and how generative AI can be utilized in SOC automation.The rapid advancements and growing variety of publicly available generative AI tools enables cybersecurity use cases for threat modeling, security awareness support, web application scanning, actionable insights, and alert fatigue prevention. However, they also came with a steep rise in the number of offensive/rogue/malicious generative AI applications. With large language models, social engineering tactics can reach new heights in the efficiency of phishing campaigns and cyber-deception via synthetic media generation (misleading deepfake images and videos, faceswapping, morphs, and voice clones). The result is a new era of cybersecurity that necessitates innovative approaches to detect and mitigate sophisticated cyberattacks, and to prevent hyper-realistic cyber-deception.This work provides a starting point for researchers and students diving into malicious chatbot use, system administrators trying to harden the security of GenAI deployments, and organizations prone to sensitive data leak through shadow AI. It also benefits SOC analysts considering generative AI for partially automating incident detection and response, and GenAI vendors working on security guardrails against malicious prompting. 71 pp. Englisch.…

  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer, 2025

    3032052491 / 9783032052490

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  • Language: English

    Published by Springer Verlag GmbH, 2025

    3032052491 / 9783032052490

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    Condition: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt.

  • Language: English

    Published by Springer Nature Switzerland AG, Cham, 2025

    3032052491 / 9783032052490

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    Paperback. Condition: new. Paperback. This book explores the most common generative AI (GenAI) tools and techniques used by malicious actors for hacking and cyber-deception, along with the security risks of large language models (LLMs). It also covers how LLM deployment and use can be secured, and how generative AI can be utilized in SOC automation.The rapid advancements and growing variety of publicly available generative AI tools enables cybersecurity use cases for threat modeling, security awareness support, web application scanning, actionable insights, and alert fatigue prevention. However, they also came with a steep rise in the number of offensive/rogue/malicious generative AI applications. With large language models, social engineering tactics can reach new heights in the efficiency of phishing campaigns and cyber-deception via synthetic media generation (misleading deepfake images and videos, faceswapping, morphs, and voice clones). The result is a new era of cybersecurity that necessitates innovative approaches to detect and mitigate sophisticated cyberattacks, and to prevent hyper-realistic cyber-deception.This work provides a starting point for researchers and students diving into malicious chatbot use, system administrators trying to harden the security of GenAI deployments, and organizations prone to sensitive data leak through shadow AI. It also benefits SOC analysts considering generative AI for partially automating incident detection and response, and GenAI vendors working on security guardrails against malicious prompting. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability.…

  • Language: English

    Published by Springer, Springer Nov 2025, 2025

    3032052491 / 9783032052490

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    Taschenbuch. Condition: Neu. This item is printed on demand - Print on Demand Titel. Neuware -This book explores the most common generative AI (GenAI) tools and techniques used by malicious actors for hacking and cyber-deception, along with the security risks of large language models (LLMs). It also covers how LLM deployment and use can be secured, and how generative AI can be utilized in SOC automation.The rapid advancements and growing variety of publicly available generative AI tools enables cybersecurity use cases for threat modeling, security awareness support, web application scanning, actionable insights, and alert fatigue prevention. However, they also came with a steep rise in the number of offensive/rogue/malicious generative AI applications. With large language models, social engineering tactics can reach new heights in the efficiency of phishing campaigns and cyber-deception via synthetic media generation (misleading deepfake images and videos, faceswapping, morphs, and voice clones). The result is a new era of cybersecurity that necessitates innovative approaches to detect and mitigate sophisticated cyberattacks, and to prevent hyper-realistic cyber-deception.This work provides a starting point for researchers and students diving into malicious chatbot use, system administrators trying to harden the security of GenAI deployments, and organizations prone to sensitive data leak through shadow AI. It also benefits SOC analysts considering generative AI for partially automating incident detection and response, and GenAI vendors working on security guardrails against malicious prompting.Springer-Verlag KG, Sachsenplatz 4-6, 1201 Wien 84 pp. Englisch.…