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Combining Machine Learning and Rules for Cybersecurity

BeginnerGuided Project

Do you want to be a cyber security expert and help safeguard digital networks and systems from malicious attacks? Then you'll love this project! By using a combination of machine learning algorithms and rule-based approaches, you will develop a powerful tool for detecting cyber attacks. You will analyze network data and identify correlations between different variables to pinpoint potential threats. Don't miss out on this exciting opportunity to learn how to analyze network data and identify the tell-tale signs of cyber attacks.

4.6 (444 Reviews)

Language

  • English

Topic

  • Artificial Intelligence

Industries

  • Information Technology

Enrollment Count

  • 2.10K

Skills You Will Learn

  • Security, Python, Machine Learning, CyberSecurity, Data Analysis

Offered By

  • IBMSkillsNetwork

Estimated Effort

  • 1.5 hours

Platform

  • SkillsNetwork

Last Update

  • May 9, 2025
About this Guided Project
This project uses machine learning and rule-based approaches to improve cyber attack detection. 
By analyzing network data and identifying correlations between variables, it enhances the accuracy and efficiency of cyber attack detection, making digital networks and systems more secure. This project provides valuable insight into network data analysis and cyber attack identification, making it a valuable first step towards becoming a cyber security expert.

A Look at the Project Ahead

After completing this lab you will be able to::
  • Understand how cyber attacks occur and identify important indicators of attacks.
  • Implement a monitoring system for attack detection using both rule-based and machine-learning approaches.
  • Learn how to visualize variables in network data.
  • Gain experience in using machine learning algorithms such as Random Forest for classification and feature ranking.
  • Enhance your knowledge and skills in cybersecurity and introduce powerful tools to equipped to detect and prevent cyber-attacks.
  • introduce strong cloud security tool IBM QRadar

What You'll Need

Your enthusiasm, a browser, and a little background in python.

Instructors

Sina Nazeri

Data Scientist at IBM

I am grateful to have had the opportunity to work as a Research Associate, Ph.D., and IBM Data Scientist. Through my work, I have gained experience in unraveling complex data structures to extract insights and provide valuable guidance.

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Joseph Santarcangelo

Senior Data Scientist at IBM

Joseph has a Ph.D. in Electrical Engineering, his research focused on using machine learning, signal processing, and computer vision to determine how videos impact human cognition. Joseph has been working for IBM since he completed his PhD.

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Contributors

Roxanne Li

Data Scientist at IBM

I am an aspiring Data Scientist at IBM with extensive theoretical/academic, research, and work experience in different areas of Machine Learning, including Classification, Clustering, Computer Vision, NLP, and Generative AI. I've exploited Machine Learning to build data products for the P&C insurance industry in the past. I also recently became an instructor of the Unsupervised Machine Learning course by IBM on Coursera!

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J.C.(Junxing) Chen

Data scientist at IBM

Data science is easy and helpful! I want to let everyone know data science and help everyone using it for everyday life! Not only being a Data science guide person but also making friends, I want to make friends with peoples like you! As a data scienist, I hope my spread data science could help my friend!

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Sheng-Kai Chen

Data Scientist

Sheng-Kai Chen is a graduate student at the University of Toronto, concentrating on Information Systems & Design. Having several experiences analyzing data for retail stores and designing small software for small businesses. Sheng-Kai was inspired to shift toward answering new challenges with machine learning and new technics.

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Artem Arutyunov

Data Scientist

Hey, Artem here! I am excited about answering new challenges with data science, machine learning and especially Reinforcement Learning. Love helping people to learn, and learn myself. Studying Math and Stats at University of Toronto, hit me up if you are from there as well.

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