Machine Learning and Emerging Technologies in Cybersecurity

Overview

The course "Machine Learning and Emerging Technologies in Cybersecurity" offers an in-depth exploration of machine learning applications in cybersecurity, focusing on techniques for threat detection and prevention. Participants will gain a solid grounding in machine learning fundamentals, including neural networks, clustering, and support vector machines, tailored specifically for cybersecurity contexts. Unique to this course is the integration of machine learning with Intrusion Detection Systems (IDS), equipping learners with practical skills to enhance threat detection capabilities. Additionally, the course examines Tor networking, providing insights into secure and anonymous communication systems, as well as the critical role of IDS within Cyber Security Incident Response Teams (CSIRTs) in enterprise environments. By the end of the course, learners will not only understand how to apply advanced machine learning techniques but also be proficient in tools like RapidMiner and Security Onion. This blend of theory and hands-on application ensures that participants leave with the skills needed to tackle real-world cybersecurity challenges effectively, making this course a vital resource for those looking to advance their careers in cybersecurity and data science.

Syllabus

Course Introduction

This course provides a comprehensive introduction to machine learning and data mining, covering key algorithms and tools like RapidMiner and Security Onion. Students will explore advanced topics such as neural networks, clustering, and support vector machines, while also learning to evaluate model performance through confusion matrices and ROC curves. Additionally, the course delves into ToR architecture, privacy concerns, and the practical installation of ToR clients. Emphasis will be placed on incident response within Computer Security Incident Response Teams (CSIRTs) and effective information-sharing practices. By the end of the course, participants will have a robust understanding of both machine learning techniques and their applications in cybersecurity.

Machine Learning I

The course delves deeper into specific approaches, including neural networks, clustering, and support vector machines (SVMs), providing students with a solid foundation in both the theory and practice of these advanced techniques.

Machine Learning II

This course explores the integration of Machine Learning (ML) algorithms into Intrusion Detection Systems (IDS) to enhance threat detection capabilities.

ToR Networking

This course provides a comprehensive understanding of The Onion Router (ToR) architectures, focusing on the critical components that make up this secure and anonymous communication system.

IDS in Context

This module explores the critical role of Intrusion Detection Systems (IDS) within Cyber Security Incident Response Teams (CSIRTs), particularly in high-volume enterprise environments.