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Machine Learning Principles for Secure Systems
1- Introduction to Machine Learning Principles for Secure Systems
Welcome to SFBS! (1:22)
How to utilize this Machine Learning Principles for Secure Systems Training Program
Introduction (4:54)
💡Tip - Follow SFBS on LinkedIn & YouTube
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2- Secure Design
Secure Design - Introduction (0:55)
Raise awareness of ML threats and risks (6:38)
Model the threats to your system (5:09)
Minimize an Adversary's Knowledge (4:37)
Analyze Vulnerabilities Against Inherent ML Threats (5:18)
💡Tip - Give 20%, Get 20%
💡Tip - Give 20%, Get 20%
3- Secure Development
Secure Development - Introduction (0:52)
Secure Your Supply Chain (5:22)
Secure your development infrastructure (4:33)
Manage the full life cycle of models and datasets (8:47)
Choose a model that maximizes security and performance (6:19)
4- Secure Deployment
Secure Deployment - Introduction (1:29)
Protect information that could be used to attack your model (5:52)
Monitor and Log User Activity (2:55)
5- Secure Operation
Secure Operation - Introduction (0:55)
Understand and mitigate the risks of using continual learning (CL) (6:45)
Appropriately sanitize inputs to your model in use (4:19)
Develop incident and vulnerability management processes (3:04)
6- End of Life
End of Life - Introduction (0:53)
Decommission Your Assets Appropriately (2:13)
Collate lessons learned and share with the community (2:01)
Claim Earned Continuing Education Credits - For Retaining Certificates (PMP, CSM, CAPM, etc.)
Claim Earned Continuing Education Credits - For Retaining Certificates (PMP, CSM, CAPM, etc.)
Bonus Lecture - Discount for our paid programs
Bonus Lecture - Discount for our paid programs
Appropriately sanitize inputs to your model in use
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