Exploring Machine Learning in Cybersecurity Workshop#
Welcome WSU Students,
Are you passionate about digital defenses against ever-evolving cyber threats? In this Western Sydney University (WSU) workshop, we will delve into the dynamic synergy between machine learning and cybersecurity.
In today’s digitally interconnected world, the realm of cybersecurity demands innovative approaches to counter sophisticated cyber threats. This immersive workshop at WSU offers a unique opportunity to delve deep into the realm of machine learning’s role in fortifying cybersecurity practices.
What to Expect:#
Explore Fundamental Concepts: Understand the core principles of machine learning and its pivotal applications within the cybersecurity domain.
Real-World Applications: Delve into practical scenarios including malware detection, anomaly identification, threat severity prediction, and more, elucidating the transformative impact of machine learning in safeguarding digital assets.
Interactive Sessions: Engage in hands-on exercises and simulations, applying machine learning techniques to tackle cybersecurity challenges under expert guidance.
Insights from Industry Leaders: Gain invaluable insights from seasoned industry professionals sharing their expertise and experiences in deploying machine learning for robust cybersecurity measures.
Table of Content#
We’ll be sharing our workshop content throughout the scheduled sessions. Initially, we’ll release a set of questions or exercises for active participation. We warmly invite you to join in and engage with the content during the workshop. Feel free to work on the provided questions or exercises as they are released. Our staff encourage you to participate and actively contributing during the workshop sessions. If there are specific formats or platforms for participation, please let us know!
- Module 0: Introduction to Jupyter Notebook and Colab
- Examples of plotting Machine Learning Model
- Example 1: Generating linear continuous data
- Example 2: Generating linearly separable binary data
- Module 1: Fundamentals of Machine Learning
- Machine Learning
- Module 2: Supervised Learning
- Exercise 1: \(k\)-Nearest Neighbours
- Exercise 2: Decision Trees
- Exercise 3: Random Forests
- Exercise 4: AdaBoost
- Module 3: Data Preprocessing and Features Selection
- Module 4: Unsupervised Learning
- Module 5: Anomaly and Intrusion Detection with Machine Learning
- Module 6: Generative AI for Cyber Security