Explore the reality behind AI and Machine Learning in cybersecurity in this 32-minute RSA Conference talk by John Pescatore, Director of SANS. Cut through the hype surrounding these technologies and discover their practical applications in reducing detection, response, and restoration times. Examine real-world examples of machine learning's effectiveness in cybersecurity, including malware prevention and detection, risk monitoring, and event analysis. Gain insights into the balance between machine automation and human intervention, and learn about the resources needed to implement these advanced techniques effectively.
AI - Machine Learning - What is Actually Working in Cybersecurity
Overview
Syllabus
Intro
Machine Learning Terminology
The First 60 Years or So...
Al Today: A "Left-Side Heavy" Hype Cycle
Machine Learning: "Peak" Heavy
Behavior-based Detection or Machine Learning?
Focusing on the Useful Parts
Marketing Use of AI/ML
Focusing on Cybersecurity
Log Entries to Events to Incidents to Action!
Cybersecurity Use of AI/ML
Practical Applications of ML: 101
Machine Learning Use Case Malware Prevention Detection Malware detection and prevention can be improved through machine learning.
ML used to monitor relationships, events, risks
Practical Applications of ML: Tools
How Much Does the Machine Do Without the Human?
TNSTAAFL: Balanced
Resources
Taught by
RSA Conference
