No Silver Bullet - Multi Contextual Threat Detection via Machine Learning

Explore multi-contextual threat detection using machine learning in this 53-minute conference talk from BSidesLV 2016. Delve into big data processing, current technologies, and the utility of machine learning in cybersecurity. Learn how to model adversaries, implement defense at scale, and build custom solutions. Discover various threat surfaces, use cases, and workflows for effective threat detection. Gain insights into exploit sequences, centralized monitoring, and labeling techniques. The presentation includes a demonstration and covers topics such as linear models, random forests, and the benefits of machine learning in cybersecurity.

Intro
Who are we
What is big data
Processing big data
Current technologies
Utility of technologies
What is Machine Learning
Modeling an adversary
Defense at scale
Building custom solutions
Search space
Benefits of ML
Linear model
Random forest
Threat Surfaces
Use Cases
Workflows
Architecture
Exploit sequence
Centralizing
Monitoring
Labeling
Demo