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MATLAB for Machine Learning

You're reading from   MATLAB for Machine Learning Unlock the power of deep learning for swift and enhanced results

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Product type Paperback
Published in Jan 2024
Publisher Packt
ISBN-13 9781835087695
Length 374 pages
Edition 2nd Edition
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Author (1):
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Giuseppe Ciaburro Giuseppe Ciaburro
Author Profile Icon Giuseppe Ciaburro
Giuseppe Ciaburro
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Table of Contents (17) Chapters Close

Preface 1. Part 1: Getting Started with Matlab
2. Chapter 1: Exploring MATLAB for Machine Learning FREE CHAPTER 3. Chapter 2: Working with Data in MATLAB 4. Part 2: Understanding Machine Learning Algorithms in MATLAB
5. Chapter 3: Prediction Using Classification and Regression 6. Chapter 4: Clustering Analysis and Dimensionality Reduction 7. Chapter 5: Introducing Artificial Neural Network Modeling 8. Chapter 6: Deep Learning and Convolutional Neural Networks 9. Part 3: Machine Learning in Practice
10. Chapter 7: Natural Language Processing Using MATLAB 11. Chapter 8: MATLAB for Image Processing and Computer Vision 12. Chapter 9: Time Series Analysis and Forecasting with MATLAB 13. Chapter 10: MATLAB Tools for Recommender Systems 14. Chapter 11: Anomaly Detection in MATLAB 15. Index 16. Other Books You May Enjoy

Creating recommender systems for network intrusion detection using MATLAB

A NIDS serves as a security mechanism that’s employed to identify and prevent unauthorized access, malicious activities, and potential threats within a computer network. It involves monitoring network traffic and analyzing it to identify any suspicious or abnormal behaviors. The main objective of network intrusion detection is to protect the network from various types of attacks, such as denial-of-service (DoS) attacks, malware infections, data leakage, unauthorized access, and other cyber threats.

There are two primary methods of network intrusion detection:

  • Signature-based detection: This method involves comparing network traffic patterns with a database of known signatures or patterns of known attacks. If a match is found, an alert is generated to notify the network administrator.
  • Anomaly-based detection: This method focuses on identifying abnormal or suspicious network behavior that...
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