Machine Learning Security Principles

Table of Contents

1. Defining Machine Learning Security
2. Mitigating Risk at Training by Validating and Maintaining Datasets
3. Mitigating Inference Risk by Avoiding Adversarial Machine Learning Attacks
4. Considering the Threat Environment
5. Keeping Your Network Clean
6. Detecting and Analyzing Anomalies
7. Dealing with Malware
8. Locating Potential Fraud
9. Defending against Hackers
10. Considering the Ramifications of Deepfakes
11. Leveraging Machine Learning against Hacking
12. Embracing and Incorporating Ethical Behavior