Securing Large Language Models Against Emerging Threats - Couverture rigide

9798337371337: Securing Large Language Models Against Emerging Threats

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ISBN 13 : 9798337371337

Editeur : Igi Global Scientific Publishing, 2025

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�diteur: Igi Global Scientific Publishing
Date d'�dition: 2025
Langue: anglais
ISBN 13: 9798337371337
Reliure: Reli�
Nombre de pages: 352
�diteur: Zangana Hewa Majeed, Omar Marwan
Coordonn�es du fabricant: non disponible
Personne responsable: GPSR Kontakt
gpsr@libri.de

Europaallee 1
Bad Hersfeld
36244
Allemagne

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Securing Large Language Models Against Emerging Threats

Edit� par Igi Global Scientific Publishing, 2025

ISBN 13 : 9798337371337

Neuf Couverture rigide

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Securing Large Language Models Against Emerging Threats (Hardcover)

Hewa Majeed Zangana

Edit� par Igi Global Scientific Publishing, 2025

ISBN 13 : 9798337371337

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Hardcover. Etat : new. Hardcover. As large language models (LLMs) become integrated into critical applications, their security emerges as a pressing concern. While these models offer capabilities in understanding and generating language, they also present new vulnerabilities that malicious actors are learning to exploit. Emerging threats challenge the integrity, confidentiality, and availability of LLM-based systems. Securing these models requires a comprehensive approach that anticipates emerging risks, blending technical safeguards with responsible deployment practices. As the adoption of LLMs increases, strengthening them against new threats becomes critical. Securing Large Language Models Against Emerging Threats explores the field of LLM security, focusing on the challenges, threats, and solutions surrounding the deployment and use of generative AI systems. It examines defense mechanisms, auditing techniques, red teaming practices, regulatory implications, and best practices for securing LLMs in real-world environments. This book covers topics such as cybercrime, smart technology, and fraud detection, and is a useful resource for security professionals, computer engineers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from our UK warehouse or from our Australian or US warehouses, depending on stock availability. N� de r�f. du vendeur 9798337371337

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Securing Large Language Models Against Emerging Threats

Edit� par IGI GLOBAL SCIENTIFIC PUBLISHING, 2025

ISBN 13 : 9798337371337

Neuf Couverture rigide

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HRD. Etat : New. New Book. Shipped from UK. Established seller since 2000. N� de r�f. du vendeur L2-9798337371337

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Securing Large Language Models Against Emerging Threats

Hewa Majeed Zangana

Edit� par IGI GLOBAL SCIENTIFIC PUBLISHING, 2025

ISBN 13 : 9798337371337

Neuf Couverture rigide

impression � la demande

Vendeur : AHA-BUCH GmbH, Einbeck, Allemagne

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Buch. Etat : Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As large language models (LLMs) become integrated into critical applications, their security emerges as a pressing concern. While these models offer capabilities in understanding and generating language, they also present new vulnerabilities that malicious actors are learning to exploit. Emerging threats challenge the integrity, confidentiality, and availability of LLM-based systems. Securing these models requires a comprehensive approach that anticipates emerging risks, blending technical safeguards with responsible deployment practices. As the adoption of LLMs increases, strengthening them against new threats becomes critical. Securing Large Language Models Against Emerging Threats explores the field of LLM security, focusing on the challenges, threats, and solutions surrounding the deployment and use of generative AI systems. It examines defense mechanisms, auditing techniques, red teaming practices, regulatory implications, and best practices for securing LLMs in real-world environments. This book covers topics such as cybercrime, smart technology, and fraud detection, and is a useful resource for security professionals, computer engineers, academicians, researchers, and scientists. N� de r�f. du vendeur 9798337371337

Contacter le vendeur