Machine Learning for Cybersecurity Cookbook

Machine Learning for Cybersecurity Cookbook

Author: Emmanuel Tsukerman

Publisher: Packt Publishing Ltd

ISBN: 9781838556341

Category: Computers

Page: 346

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Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key Features Manage data of varying complexity to protect your system using the Python ecosystem Apply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineering Automate your daily workflow by addressing various security challenges using the recipes covered in the book Book Description 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. 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. 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. What you will learn Learn how to build malware classifiers to detect suspicious activities Apply ML to generate custom malware to pentest your security Use ML algorithms with complex datasets to implement cybersecurity concepts Create neural networks to identify fake videos and images Secure your organization from one of the most popular threats – insider threats Defend against zero-day threats by constructing an anomaly detection system Detect web vulnerabilities effectively by combining Metasploit and ML Understand how to train a model without exposing the training data Who this book is for This book is for cybersecurity professionals and security researchers who are looking to implement the latest machine learning techniques to boost computer security, and gain insights into securing an organization using red and blue team ML. This recipe-based book will also be useful for data scientists and machine learning developers who want to experiment with smart techniques in the cybersecurity domain. Working knowledge of Python programming and familiarity with cybersecurity fundamentals will help you get the most out of this book.
Machine Learning for Cybersecurity Cookbook
Language: en
Pages: 346
Authors: Emmanuel Tsukerman
Categories: Computers
Type: BOOK - Published: 2019-11-25 - Publisher: Packt Publishing Ltd

Learn how to apply modern AI to create powerful cybersecurity solutions for malware, pentesting, social engineering, data privacy, and intrusion detection Key Features Manage data of varying complexity to protect your system using the Python ecosystem Apply ML to pentesting, malware, data privacy, intrusion detection system(IDS) and social engineering Automate
Hands-On Artificial Intelligence for Cybersecurity
Language: en
Pages: 342
Authors: Alessandro Parisi
Categories: Computers
Type: BOOK - Published: 2019-08-02 - Publisher:

Build smart cybersecurity systems with the power of machine learning and deep learning to protect your corporate assets Key Features Identify and predict security threats using artificial intelligence Develop intelligent systems that can detect unusual and suspicious patterns and attacks Learn how to test the effectiveness of your AI cybersecurity
Handbook of Research on Advancing Cybersecurity for Digital Transformation
Language: en
Pages: 460
Authors: Sandhu, Kamaljeet
Categories: Computers
Type: BOOK - Published: 2021-06-18 - Publisher: IGI Global

Cybersecurity has been gaining serious attention and recently has become an important topic of concern for organizations, government institutions, and largely for people interacting with digital online systems. As many individual and organizational activities continue to grow and are conducted in the digital environment, new vulnerabilities have arisen which have
Malware Analysis Using Artificial Intelligence and Deep Learning
Language: en
Pages: 651
Authors: Mark Stamp, Mamoun Alazab, Andrii Shalaginov
Categories: Computers
Type: BOOK - Published: 2020-12-20 - Publisher: Springer Nature

​This book is focused on the use of deep learning (DL) and artificial intelligence (AI) as tools to advance the fields of malware detection and analysis. The individual chapters of the book deal with a wide variety of state-of-the-art AI and DL techniques, which are applied to a number of
Machine Learning with Amazon SageMaker Cookbook
Language: en
Pages: 762
Authors: Joshua Arvin Lat
Categories: Computers
Type: BOOK - Published: 2021-10-22 - Publisher: Packt Publishing Ltd

A step-by-step solution-based guide to preparing building, training, and deploying high-quality machine learning models with Amazon SageMaker Key Features Perform ML experiments with built-in and custom algorithms in SageMaker Explore proven solutions when working with TensorFlow, PyTorch, Hugging Face Transformers, and scikit-learn Use the different features and capabilities of SageMaker