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Hands-On Machine Learning for Cybersecurity

You're reading from Hands-On Machine Learning for Cybersecurity

Product type Book

Published in Dec 2018

Publisher Packt

ISBN-13 9781788992282

Pages 318 pages

Edition 1st Edition

Languages

Concepts

Machine Learning

Authors (2):

Soma Halder

Sinan Ozdemir

View More author details

Table of Contents (13) Chapters

Preface

1. Basics of Machine Learning in Cybersecurity

2. Time Series Analysis and Ensemble Modeling

3. Segregating Legitimate and Lousy URLs

4. Knocking Down CAPTCHAs

5. Using Data Science to Catch Email Fraud and Spam

6. Efficient Network Anomaly Detection Using k-means

7. Decision Tree and Context-Based Malicious Event Detection

8. Catching Impersonators and Hackers Red Handed

9. Changing the Game with TensorFlow

10. Financial Fraud and How Deep Learning Can Mitigate It

11. Case Studies

12. Other Books You May Enjoy

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Predicting DDoS attacks

Now that we have identified a seasonality, the trend in the network data will baseline the data by fitting to a stochastic model. We have already defined systematic parameters, and we will apply them next.

ARMA

This is a weak stochastic stationary process, such that, when provided with a time series X_t, ARMA helps to forecast future values with respect to current values. ARMA consists of two actions:

The autoregression (p)
The moving average (q)

C = Constant
E_t = White noise
θ = Parameters

ARIMA

ARIMA is a generalized version of ARMA...

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Authors (2)

Soma Halder

Soma Halder is the data science lead of the big data analytics group at Reliance Jio Infocomm Ltd, one of India's largest telecom companies. She specializes in analytics, big data, cybersecurity, and machine learning. She has approximately 10 years of machine learning experience, especially in the field of cybersecurity. She studied at the University of Alabama, Birmingham where she did her master's with an emphasis on Knowledge discovery and Data Mining and computer forensics. She has worked for Visa, Salesforce, and AT&T. She has also worked for start-ups, both in India and the US (E8 Security, Headway ai, and Norah ai). She has several conference publications to her name in the field of cybersecurity, machine learning, and deep learning.

See other products by Soma Halder

Sinan Ozdemir

Sinan is an active lecturer focusing on large language models and a former lecturer of data science at the Johns Hopkins University. He is the author of multiple textbooks on data science and machine learning including "Quick Start Guide to LLMs". Sinan is currently the founder of LoopGenius which uses AI to help people and businesses boost their sales and was previously the founder of the acquired Kylie.ai, an enterprise-grade conversational AI platform with RPA capabilities. He holds a Master's Degree in Pure Mathematics from Johns Hopkins University and is based in San Francisco.

See other products by Sinan Ozdemir

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