12 Advanced machine learning analysis

 

This chapter covers

  • The use of machine learning in cybersecurity
  • Key machine learning algorithms for security applications
  • Practical applications of AI in cybersecurity
  • Implementing AI models in security systems
  • Evaluating AI performance in cybersecurity

This chapter examines the transformative role that artificial intelligence (AI) and machine learning (ML) play in cybersecurity. AI and ML have changed the way organizations approach threat detection, response, and risk management. By learning from historical data and adapting to new patterns, AI can anticipate, identify, and respond to cyber threats far more rapidly and efficiently than traditional methods.

Here, we will explore some algorithms driving AI-powered cybersecurity solutions, their applications in real-world scenarios, and the practical steps required to implement and evaluate these models. Although AI and ML are complex technologies, this chapter aims to break them down into understandable components, providing security professionals with the knowledge they need to adopt AI-driven solutions effectively.

12.1 Code requirements

12.1.1 What is AI

12.2 DBSCAN for threat detection

12.2.1 DBSCAN example

12.3 Random forest and SVM for threat detection

12.3.1 Random forest and SVM exercise

12.3.2 Isolation forest and autoencoders exercise

12.4 Natural language processing

12.4.1 NLP exercise

12.5 Deep learning

12.5.1 Deep learning exercise

12.6 Reinforcement learning

12.6.1 Reinforcement learning example in Python code

Summary