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Starts 16 June 2025 11:11

Ends 16 June 2025

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Contextual Threat Intelligence - Building a Data Science Capability into the Hunt Team

Learn to build a data science capability into your threat hunting team, enhancing intelligence gathering and analysis for improved cybersecurity operations and threat detection.
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Overview

Learn to build a data science capability into your threat hunting team, enhancing intelligence gathering and analysis for improved cybersecurity operations and threat detection.

Syllabus

  • Introduction to Contextual Threat Intelligence
  • Definition and significance in cybersecurity
    Overview of threat hunting and its role in modern security operations
  • Fundamentals of Data Science in Threat Intelligence
  • Basics of data science relevant to cybersecurity
    Key concepts: machine learning, statistical analysis, data preprocessing
  • Building a Data Science Capability
  • Integrating data science into hunting workflows
    Tools and technologies for data-driven threat intelligence
    Team roles and required skills
  • Data Collection and Management
  • Sources of threat intelligence data
    Data handling, storage, and preprocessing techniques
    Ensuring data quality and relevance
  • Data Analysis Techniques for Threat Detection
  • Overview of analytical methods and algorithms
    Use of statistical models and machine learning in detecting threats
    Real-time data analysis for proactive threat hunting
  • Enhancing Threat Intelligence with Machine Learning
  • Introduction to machine learning models for threat analysis
    Training, validation, and deployment of models
    Case studies of machine learning applications in threat intelligence
  • Contextualizing Threat Intelligence
  • Adding context to data: geopolitical, temporal, and situational factors
    Building and using threat intelligence frameworks
  • Visualization and Reporting
  • Tools and techniques for visualizing security data
    Effective communication of findings to stakeholders
    Creating actionable reports from data insights
  • Operationalizing Data Science in Threat Hunting
  • Building pipelines and automating processes
    Continuous improvement of threat detection capabilities
    Best practices and common challenges
  • Conclusion and Next Steps
  • Review of key concepts
    Roadmap for implementing data science capabilities
    Further learning resources and certifications
  • Final Project
  • Apply learned concepts to build a data science-driven threat intelligence strategy.

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Conference Talks