Machine Learning for Cybersecurity Cookbook: Over 80 Recipes to Implement Machine Learning Algorithms for Building Security Systems Using Python (Record no. 49559)

MARC details
000 -LEADER
fixed length control field 01882 a2200181 4500
005 - DATE AND TIME OF LATEST TRANSACTION
control field 20250226122925.0
020 ## - INTERNATIONAL STANDARD BOOK NUMBER
International Standard Book Number 9781789614671
082 ## - DEWEY DECIMAL CLASSIFICATION NUMBER
Classification number 005.8 TSU
100 ## - MAIN ENTRY--PERSONAL NAME
Personal name Tsukerman, Emmanuel
245 ## - TITLE STATEMENT
Title Machine Learning for Cybersecurity Cookbook: Over 80 Recipes to Implement Machine Learning Algorithms for Building Security Systems Using Python
260 ## - PUBLICATION, DISTRIBUTION, ETC. (IMPRINT)
Name of publisher, distributor, etc Packt publishers
Date of publication, distribution, etc 2019
Place of publication, distribution, etc Birmingham
300 ## - PHYSICAL DESCRIPTION
Extent 329
520 ## - SUMMARY, ETC.
Summary, etc Organizations today face a major threat in terms of cybersecurity, from malicious URLs to credential reuse, and having robust security systems can make all the difference. With this book, you'll learn how to use Python libraries such as TensorFlow and scikit-learn to implement the latest artificial intelligence (AI) techniques and handle challenges faced by cybersecurity researchers.<br/><br/>You'll begin by exploring various machine learning (ML) techniques and tips for setting up a secure lab environment. Next, you'll implement key ML algorithms such as clustering, gradient boosting, random forest, and XGBoost. The book will guide you through constructing classifiers and features for malware, which you'll train and test on real samples. As you progress, you'll build self-learning, reliant systems to handle cybersecurity tasks such as identifying malicious URLs, spam email detection, intrusion detection, network protection, and tracking user and process behavior. Later, you'll apply generative adversarial networks (GANs) and autoencoders to advanced security tasks. Finally, you'll delve into secure and private AI to protect the privacy rights of consumers using your ML models.<br/><br/>By the end of this book, you'll have the skills you need to tackle real-world problems faced in the cybersecurity domain using a recipe-based approach.
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Cybersecurity
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Machine Learning
650 ## - SUBJECT ADDED ENTRY--TOPICAL TERM
Topical term or geographic name as entry element Python
942 ## - ADDED ENTRY ELEMENTS (KOHA)
Koha item type Book
Source of classification or shelving scheme Dewey Decimal Classification

No items available.