Applying Machine Learning to User Behavior Anomaly Analysis
Hack In The Box Security Conference via YouTube
Overview
Syllabus
Intro
OUTLINE
USER BEHAVIOR ANALYTICS
MACHINE LEARNING
DATA SOURCES
DATA FORMATS
DATA NORMALIZATION: BEFORE
DATA NORMALIZATION: AFTER
ERP SECURITY LOGGING
THREAT MODEL Use Cases
ANOMALY TYPES
ANOMALIES VS. THREATS
STATIC ANOMALY DETECTION
CONTEXT BUILDING
CONTEXT THRESHOLD
CONTEXT MATCHING
ANOMALY ANALYSIS
TEMPORAL ANOMALY DETECTION
FEATURE ENGINEERING
FEATURE SELECTION
FEATURE ENCODING
MODEL IMPLEMENTATION
MODEL MEMORY
MODEL DESIGN Architecture
MODEL PARAMETERS
SEQUENCE LENGTH
KNOWLEDGE BASE SORTING
ADAPTIVE THRESHOLD
CONCLUSIONS
Taught by
Hack In The Box Security Conference