Machine learning security principles use various methods to keep data, networks, users, and applications safe from prying eyes

Thwart hackers by preventing, detecting, and misdirecting access before they can plant malware, obtain credentials, engage in fraud, modify data, poison models, corrupt users, eavesdrop, and otherwise ruin your dayKey Features:Discover how hackers rely on misdirection and deep fakes to fool even the...

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Detalles Bibliográficos
Otros Autores: Mueller, John, 1958- author (author)
Formato: Libro electrónico
Idioma:Inglés
Publicado: Birmingham : Packt Publishing 2022.
Materias:
Ver en Biblioteca Universitat Ramon Llull:https://discovery.url.edu/permalink/34CSUC_URL/1im36ta/alma991009711801806719
Tabla de Contenidos:
  • Table of Contents Defining Machine Learning Security Mitigating Risk at Training by Validating and Maintaining Datasets Mitigating Inference Risk by Avoiding Adversarial Machine Learning Attacks Considering the Threat Environment Keeping Your Network Clean Detecting and Analyzing Anomalies Dealing with Malware Locating Potential Fraud Defending against Hackers Considering the Ramifications of Deepfakes Leveraging Machine Learning against Hacking Embracing and Incorporating Ethical Behavior.