Course Overview

The number of cyber-attacks is growing exponentially, and every cyber-attack utilizes some malicious code and some malware. Companies around the world are losing billions of dollars every year because of information security breaches caused by malware. The companies invest more in protecting and analyzing constant malware threats, being in constant need of incident responders. Malware analysis is the study or process of determining the functionality, origin, and potential impact of a given malware samples such as a virus, worm, trojan horse, rootkit, or backdoor.

This course will equip you with skills and tools that will allow you to be an incident responder and identify and analyze attacks and the malware used in them. You will start with examining what malware is, how it developed over history, what types of malware there are as well as what are the tools and how to perform static and dynamic malware analysis. You will also venture further into how model malware and intrusion detection tools work and how AI and machine learning can be utilized to augment malware analysis and detection. 

By the end of the course, you will be equipped to respond to incidents, analyze malware and develop algorithms that will help you with these tasks.

What You Will Learn

  • History of malware and malicious software on PC.
  • You will learn what is virus, worm, Trojan, rootkit, ransomware, mobile malicious code, etc.
  • Learn how malicious software work and propagate, how they use exploits.
  • Explore how to build your own malware analysis lab.
  • Discover how to perform static and dynamic malware analysis.
  • Learn how to apply your skills to reverse engineer non-malicious software and gain insight into how they operate.
  • Gain knowledge about how AI and machine learning can help to detect malware.
  • Explore fingerprinting malware and reverse engineer it using several tools.

Program Curriculum

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Instructor

Dr. Nikola Milosevic Milosevic

Dr Nikola Milosevic has extensive experience as a researcher in cybersecurity, as well as in artificial intelligence and has written a number of papers on these topics that are published in relevant journals. Nikola gained his PhD in computer science from the University of Manchester, where he also worked as a research fellow and teaching assistant. He also has experience as a university lecturer teaching master courses in information security, malware analysis and reverse engineering at the University of Salford. In addition to his academic career, Nikola has experience in the industry and at relevant cyber security open source organizations. He was OWASP (Open Web Application Security Project) local chapter leader in Belgrade and Manchester. Also, he was OWASP project leader in the OWASP Seraphimdroid project, a mobile security and privacy protection app.

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