Pakshad Puya (24 results)

Condition: New.

Condition: New.

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

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

Paperback. Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

HRD. Condition: New. New Book. Shipped from UK. Established seller since 2000.

Condition: New.

Condition: As New. Unread book in perfect condition.

Condition: As New. Unread book in perfect condition.

Hardback. Condition: New.

Paperback. Condition: New.

Hardback. Condition: New.

Paperback. Condition: new. Paperback. As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Hardcover. Condition: new. Hardcover. As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, academicians, researchers, and scientists. This item is printed on demand. Shipping may be from multiple locations in the US or from the UK, depending on stock availability.…

Paperback. Condition: new. Paperback. As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, 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.…

Taschenbuch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, academicians, researchers, and scientists.…

Hardcover. Condition: new. Hardcover. As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, 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.…

Buch. Condition: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, academicians, researchers, and scientists.…

Paperback. Condition: new. Paperback. As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, academicians, researchers, and scientists. 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.…

Taschenbuch. Condition: Neu. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs | Puya Pakshad (u. a.) | Taschenbuch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337382531 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand. …

Hardcover. Condition: new. Hardcover. As AI systems and large language models (LLMs) become integrated into decision-making, communication, and automation workflows, their security becomes a pressing concern. Despite their performance, these models have vulnerabilities that can be exploited through adversarial techniques like prompt manipulation, data exploitation, and cyber-attacks. These exploits undermine system reliability while posing risks to privacy, misinformation, and safety. Examining the vulnerabilities of AI and LLMs, alongside methods used to exploit them, may further reveal limitations of current models and help develop more resilient, trustworthy AI systems. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs explores AI security, bridging governance, policy, compliance, and zero-trust strategy with AI-driven defense, detection, and engineering. It examines LLM vulnerabilities and security models, addressing responsible AI adoption, data privacy compliance, and global policy alignment. This book covers topics such as prompt manipulation, threat detection, and AI governance, and is a useful resource for engineers, policymakers, academicians, researchers, and scientists. 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.…

Buch. Condition: Neu. Examining Vulnerabilities and Adversarial Exploitation of AI and LLMs | Puya Pakshad (u. a.) | Buch | Englisch | 2026 | IGI GLOBAL SCIENTIFIC PUBLISHING | EAN 9798337382524 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.…