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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 day Key Features Discover how hackers rely on misdirection and deep fakes to fool even th...
| Clasificación: | Libro Electrónico |
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| Autor principal: | |
| Formato: | Electrónico eBook |
| Idioma: | Inglés |
| Publicado: |
Birmingham :
Packt Publishing,
2022.
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| Temas: | |
| Acceso en línea: | Texto completo (Requiere registro previo con correo institucional) |
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.