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Study mode:
on
1
Intro
2
Who are we
3
What is big data
4
Processing big data
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Current technologies
6
Utility of technologies
7
What is Machine Learning
8
Modeling an adversary
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Defense at scale
10
Building custom solutions
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Search space
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Benefits of ML
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Linear model
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Random forest
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Threat Surfaces
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Use Cases
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Workflows
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Architecture
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Exploit sequence
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Centralizing
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Monitoring
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Labeling
23
Demo
Description:
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.

No Silver Bullet - Multi Contextual Threat Detection via Machine Learning

BSidesLV
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