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    Adversarial AI Attacks, Mitigations, and Defense Strategies. A cybersecurity professional's guide to AI attacks, threat modeling, and securing AI with MLSecOps John Sotiropoulos

    (ebook) (audiobook) (audiobook) Książka w języku angielskim
    Adversarial AI Attacks, Mitigations, and Defense Strategies. A cybersecurity professional's guide to AI attacks, threat modeling, and securing AI with MLSecOps John Sotiropoulos - okladka książki

    Adversarial AI Attacks, Mitigations, and Defense Strategies. A cybersecurity professional's guide to AI attacks, threat modeling, and securing AI with MLSecOps John Sotiropoulos - okladka książki

    Adversarial AI Attacks, Mitigations, and Defense Strategies. A cybersecurity professional's guide to AI attacks, threat modeling, and securing AI with MLSecOps John Sotiropoulos - audiobook MP3

    Adversarial AI Attacks, Mitigations, and Defense Strategies. A cybersecurity professional's guide to AI attacks, threat modeling, and securing AI with MLSecOps John Sotiropoulos - audiobook CD

    Autor:
    John Sotiropoulos
    Wydawnictwo:
    Packt Publishing (Z chęcią przeczytam książkę w języku polskim)
    Ocena:
    Bądź pierwszym, który oceni tę książkę
    Stron:
    586
    Dostępne formaty:
         PDF
         ePub
    Adversarial attacks trick AI systems with malicious data, creating new security risks by exploiting how AI learns. This challenges cybersecurity as it forces us to defend against a whole new kind of threat. This book demystifies adversarial attacks and equips cybersecurity professionals with the skills to secure AI technologies, moving beyond research hype or business-as-usual strategies.
    The strategy-based book is a comprehensive guide to AI security, presenting a structured approach with practical examples to identify and counter adversarial attacks. This book goes beyond a random selection of threats and consolidates recent research and industry standards, incorporating taxonomies from MITRE, NIST, and OWASP. Next, a dedicated section introduces a secure-by-design AI strategy with threat modeling to demonstrate risk-based defenses and strategies, focusing on integrating MLSecOps and LLMOps into security systems. To gain deeper insights, you’ll cover examples of incorporating CI, MLOps, and security controls, including open-access LLMs and ML SBOMs. Based on the classic NIST pillars, the book provides a blueprint for maturing enterprise AI security, discussing the role of AI security in safety and ethics as part of Trustworthy AI.
    By the end of this book, you’ll be able to develop, deploy, and secure AI systems effectively.

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    O autorze książki

    John Sotiropoulos is a Senior Security Architect at Kainos where he is responsible for AI Security and works to secure national-scale systems in government, regulators, and healthcare. John has gained extensive experience in building and securing systems through roles such as Developer, CTO, VP of Engineering, and Chief Architect.
    A Core Team member of the OWASP Top 10 for LLM Apps and AI Exchange, he leads standards alignment for both projects with other standards organizations and national cybersecurity agencies. He is the OWASP lead at the US AI Safety Institute Consortium and part of the Task Force on Deepfake detection.
    An avid geek and marathon runner, he is passionate about enabling builders and defenders to create a safer future.

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