Cyber Threat Intelligence and Adversarial Risk Analysis

This module provides an in-depth understanding of techniques for detecting, responding to, and defeating Advanced Persistent Threats (APT) and malware campaigns using artificial intelligence and data mining techniques. It enables students to identify, extract, and leverage intelligence from different types of cyber threat actors in a lawful and ethical manner.

Upon successful completion of this course, students will have demonstrated the ability to:
1. Recognize and utilize concepts of cyber threat intelligence to detect and defeat Advanced Persistent Threat (APT) actors and adversarial machine learning techniques;
2. Analyze both successful and unsuccessful advanced cyber intrusion attacks and malware campaigns using artificial intelligence and data mining techniques;
3. Leverage intelligence to build profiles of different adversarial groups and analyse risks associated with different threat actors;
4. Develop a threat intelligence report that justifies threat attribution based on analysis of intrusion artefacts;
5. Analyse and integrate ethics, regulations, and best practices regarding collection, analysis, and sharing of intelligence data and intelligence activities; and
6. Work collaboratively in teams to conduct research and communicate rational and reasoned arguments using appropriate methods.

  • -CEOs
  • -CTOs
  • -COOs
  • -Chief Data Officers
  • -Chief Information Officers
  • -Chief Innovation Officers
  • -Chief Digital Officers
  • -CxOs (Analytics, Data, Information, Innovation, Technology)
 

This module provides an in-depth understanding of techniques for detecting, responding to, and defeating Advanced Persistent Threats (APT) and malware campaigns using artificial intelligence and data mining techniques. It enables students to identify, extract, and leverage intelligence from different types of cyber threat actors in a lawful and ethical manner.

Session 1: Introduction to cyber threat intelligence and understanding ethics, regulations, and best practices for cyber threat intelligence
Session 2-4: Foundation of cyber threat intelligence and applied machine learning
Session 5,6: Adversarial machine learning and advanced malware analysis
Session 7,8: Analysis of web-based and document-based malware
Session 9,10: Cyber threat modelling and adversarial risk analysis
Session 11,12: Tactical and operational threat intelligence

– Fall 2019, University of Guelph, Master of Cyber Security Program, More Details