Mastering Linux Security and Hardening. A practical guide to protecting your Linux system from cyber attacks - Third Edition

Donald A. Tevault

The third edition of Mastering Linux Security and Hardening is an updated, comprehensive introduction to implementing the latest Linux security measures, using the latest versions of Ubuntu and AlmaLinux.In this new edition, you will learn how to set up a practice lab, create user accounts with appropriate privilege levels, protect sensitive data with permissions settings and encryption, and configure a firewall with the newest firewall technologies. You’ll also explore how to use sudo to set up administrative accounts with only the privileges required to do a specific job, and you’ll get a peek at the new sudo features that have been added over the past couple of years. You’ll also see updated information on how to set up a local certificate authority for both Ubuntu and AlmaLinux, as well as how to automate system auditing. Other important skills that you’ll learn include how to automatically harden systems with OpenSCAP, audit systems with auditd, harden the Linux kernel configuration, protect your systems from malware, and perform vulnerability scans of your systems. As a bonus, you’ll see how to use Security Onion to set up an Intrusion Detection System.By the end of this new edition, you will confidently be able to set up a Linux server that will be secure and harder for malicious actors to compromise.

Mastering Linux Security and Hardening. Protect your Linux systems from intruders, malware attacks, and other cyber threats - Second Edition

Donald A. Tevault

From creating networks and servers to automating the entire working environment, Linux has been extremely popular with system administrators for the last couple of decades. However, security has always been a major concern. With limited resources available in the Linux security domain, this book will be an invaluable guide in helping you get your Linux systems properly secured.Complete with in-depth explanations of essential concepts, practical examples, and self-assessment questions, this book begins by helping you set up a practice lab environment and takes you through the core functionalities of securing Linux. You'll practice various Linux hardening techniques and advance to setting up a locked-down Linux server. As you progress, you will also learn how to create user accounts with appropriate privilege levels, protect sensitive data by setting permissions and encryption, and configure a firewall. The book will help you set up mandatory access control, system auditing, security profiles, and kernel hardening, and finally cover best practices and troubleshooting techniques to secure your Linux environment efficiently.By the end of this Linux security book, you will be able to confidently set up a Linux server that will be much harder for malicious actors to compromise.

Mastering Linux Security and Hardening. Secure your Linux server and protect it from intruders, malware attacks, and other external threats

Donald A. Tevault

This book has extensive coverage of techniques that will help prevent attackers from breaching your system, by building a much more secure Linux environment. You will learn various security techniques such as SSH hardening, network service detection, setting up firewalls, encrypting file systems, protecting user accounts, authentication processes, and so on. Moving forward, you will also develop hands-on skills with advanced Linux permissions, access control, special modes, and more. Lastly, this book will also cover best practices and troubleshooting techniques to get your work done efficiently.By the end of this book, you will be confident in delivering a system that will be much harder to compromise.

Mastering Linux Shell Scripting. A practical guide to Linux command-line, Bash scripting, and Shell programming - Second Edition

Mokhtar Ebrahim, Andrew Mallett

In this book, you’ll discover everything you need to know to master shell scripting and make informed choices about the elements you employ.Grab your favorite editor and start writing your best Bash scripts step by step. Get to grips with the fundamentals of creating and running a script in normal mode, and in debug mode. Learn about various conditional statements' code snippets, and realize the power of repetition and loops in your shell script. You will also learn to write complex shell scripts. This book will also deep dive into file system administration, directories, and system administration like networking, process management, user authentications, and package installation and regular expressions. Towards the end of the book, you will learn how to use Python as a BASH Scripting alternative. By the end of this book, you will know shell scripts at the snap of your fingers and will be able to automate and communicate with your system with keyboard expressions.

Mastering Linux Shell Scripting. Master the complexities of Bash shell scripting and unlock the power of shell for your enterprise

Andrew Mallett

Shell scripting is a quick method to prototype a complex application or a problem by automating tasks when working on Linux-based systems. Using both simple one-line commands and command sequences complex problems can be solved with ease, from text processing to backing up sysadmin tools.In this book, you’ll discover everything you need to know to master shell scripting and make informed choices about the elements you employ. Get to grips with the fundamentals of creating and running a script in normal mode, and in debug mode. Learn about various conditional statements' code snippets, and realize the power of repetition and loops in your shell script. Implement functions and edit files using the Stream Editor, script in Perl, program in Python – as well as complete coverage of other scripting languages to ensure you can choose the best tool for your project.

Mastering LOB Development for Silverlight 5: A Case Study in Action. Develop a full LOB Silverlight 5 application from scratch with the help of expert advice and an accompanying case study with this book and

Jose Fernando Almoguera, Reyes Garc?É!!=a Rosado, Sebastian Stehle, Pablo N?É!??É!+-ez Navarro, ...

Microsoft Silverlight is fully established as a powerful tool for creating and delivering Rich Internet Applications and media experiences on the Web. This book will help you dive straight into utilizing Silverlight 5, which now more than ever is a top choice in the Enterprise for building Business Applications. Mastering LOB Development for Silverlight 5: A Case Study in Action focuses on the development of a complete Silverlight 5 LOB application, helping you to take advantage of the powerful features available along with expert advice. Fully focused on LOB development, this expert guide takes you from the beginning of designing and implementing a Silverlight 5 LOB application, all the way through to completion. Accompanied by a gradually built upon case study, you will learn about data access via RIA and Web services, architecture with MEF and MVVM applied to LOB development, testing and error control, and much more.With Mastering LOB Development for Silverlight 5: A Case Study in Action in hand, you will be fully equipped to expertly develop your own Silverlight Line of Business application, without dwelling on the basics of Enterprise Silverlight development.

Mastering Lumion 3D. Master the art of creating real-time 3D architectural visualizations using Lumion 3D

Ciro Cardoso

Mastering Machine Learning Algorithms. Expert techniques for implementing popular machine learning algorithms, fine-tuning your models, and understanding how they work - Second Edition

Giuseppe Bonaccorso

Mastering Machine Learning Algorithms, Second Edition helps you harness the real power of machine learning algorithms in order to implement smarter ways of meeting today's overwhelming data needs. This newly updated and revised guide will help you master algorithms used widely in semi-supervised learning, reinforcement learning, supervised learning, and unsupervised learning domains.You will use all the modern libraries from the Python ecosystem – including NumPy and Keras – to extract features from varied complexities of data. Ranging from Bayesian models to the Markov chain Monte Carlo algorithm to Hidden Markov models, this machine learning book teaches you how to extract features from your dataset, perform complex dimensionality reduction, and train supervised and semi-supervised models by making use of Python-based libraries such as scikit-learn. You will also discover practical applications for complex techniques such as maximum likelihood estimation, Hebbian learning, and ensemble learning, and how to use TensorFlow 2.x to train effective deep neural networks.By the end of this book, you will be ready to implement and solve end-to-end machine learning problems and use case scenarios.

Mastering Machine Learning Algorithms. Expert techniques to implement popular machine learning algorithms and fine-tune your models

Giuseppe Bonaccorso

Machine learning is a subset of AI that aims to make modern-day computer systems smarter and more intelligent. The real power of machine learning resides in its algorithms, which make even the most difficult things capable of being handled by machines. However, with the advancement in the technology and requirements of data, machines will have to be smarter than they are today to meet the overwhelming data needs; mastering these algorithms and using them optimally is the need of the hour.Mastering Machine Learning Algorithms is your complete guide to quickly getting to grips with popular machine learning algorithms. You will be introduced to the most widely used algorithms in supervised, unsupervised, and semi-supervised machine learning, and will learn how to use them in the best possible manner. Ranging from Bayesian models to the MCMC algorithm to Hidden Markov models, this book will teach you how to extract features from your dataset and perform dimensionality reduction by making use of Python-based libraries such as scikit-learn v0.19.1. You will also learn how to use Keras and TensorFlow 1.x to train effective neural networks.If you are looking for a single resource to study, implement, and solve end-to-end machine learning problems and use-cases, this is the book you need.

Mastering Machine Learning for Penetration Testing. Develop an extensive skill set to break self-learning systems using Python

Chiheb Chebbi

Cyber security is crucial for both businesses and individuals. As systems are getting smarter, we now see machine learning interrupting computer security. With the adoption of machine learning in upcoming security products, it’s important for pentesters and security researchers to understand how these systems work, and to breach them for testing purposes. This book begins with the basics of machine learning and the algorithms used to build robust systems. Once you’ve gained a fair understanding of how security products leverage machine learning, you'll dive into the core concepts of breaching such systems. Through practical use cases, you’ll see how to find loopholes and surpass a self-learning security system. As you make your way through the chapters, you’ll focus on topics such as network intrusion detection and AV and IDS evasion. We’ll also cover the best practices when identifying ambiguities, and extensive techniques to breach an intelligent system.By the end of this book, you will be well-versed with identifying loopholes in a self-learning security system and will be able to efficiently breach a machine learning system.

Mastering Machine Learning on AWS. Advanced machine learning in Python using SageMaker, Apache Spark, and TensorFlow

Dr. Saket S.R. Mengle, Maximo Gurmendez

Amazon Web Services (AWS) is constantly driving new innovations that empower data scientists to explore a variety of machine learning (ML) cloud services. This book is your comprehensive reference for learning and implementing advanced ML algorithms in AWS cloud.As you go through the chapters, you’ll gain insights into how these algorithms can be trained, tuned, and deployed in AWS using Apache Spark on Elastic Map Reduce (EMR), SageMaker, and TensorFlow. While you focus on algorithms such as XGBoost, linear models, factorization machines, and deep nets, the book will also provide you with an overview of AWS as well as detailed practical applications that will help you solve real-world problems. Every application includes a series of companion notebooks with all the necessary code to run on AWS. In the next few chapters, you will learn to use SageMaker and EMR Notebooks to perform a range of tasks, right from smart analytics and predictive modeling through to sentiment analysis. By the end of this book, you will be equipped with the skills you need to effectively handle machine learning projects and implement and evaluate algorithms on AWS.

Mastering Machine Learning with R. Advanced machine learning techniques for building smart applications with R 3.5 - Third Edition

Cory Lesmeister

Given the growing popularity of the R-zerocost statistical programming environment, there has never been a better time to start applying ML to your data. This book will teach you advanced techniques in ML ,using? the latest code in R 3.5. You will delve into various complex features of supervised learning, unsupervised learning, and reinforcement learning algorithms to design efficient and powerful ML models. This newly updated edition is packed with fresh examples covering a range of tasks from different domains. Mastering Machine Learning with R starts by showing you how to quickly manipulate data and prepare it for analysis. You will explore simple and complex models and understand how to compare them. You’ll also learn to use the latest library support, such as TensorFlow and Keras-R, for performing advanced computations. Additionally, you’ll explore complex topics, such as natural language processing (NLP), time series analysis, and clustering, which will further refine your skills in developing applications. Each chapter will help you implement advanced ML algorithms using real-world examples. You’ll even be introduced to reinforcement learning, along with its various use cases and models. In the concluding chapters, you’ll get a glimpse into how some of these blackbox models can be diagnosed and understood. By the end of this book, you’ll be equipped with the skills to deploy ML techniques in your own projects or at work.

Mastering Machine Learning with R. Advanced prediction, algorithms, and learning methods with R 3.x - Second Edition

Cory Lesmeister

This book will teach you advanced techniques in machine learning with the latest code in R 3.3.2. You will delve into statistical learning theory and supervised learning; design efficient algorithms; learn about creating Recommendation Engines; use multi-class classification and deep learning; and more.You will explore, in depth, topics such as data mining, classification, clustering, regression, predictive modeling, anomaly detection, boosted trees with XGBOOST, and more. More than just knowing the outcome, you’ll understand how these concepts work and what they do.With a slow learning curve on topics such as neural networks, you will explore deep learning, and more. By the end of this book, you will be able to perform machine learning with R in the cloud using AWS in various scenarios with different datasets.

Mastering Machine Learning with R. Master machine learning techniques with R to deliver insights for complex projects

Cory Lesmeister

Mastering Machine Learning with scikit-learn. Apply effective learning algorithms to real-world problems using scikit-learn - Second Edition

Gavin Hackeling

Machine learning is the buzzword bringing computer science and statistics together to build smart and efficient models. Using powerful algorithms and techniques offered by machine learning you can automate any analytical model.This book examines a variety of machine learning models including popular machine learning algorithms such as k-nearest neighbors, logistic regression, naive Bayes, k-means, decision trees, and artificial neural networks. It discusses data preprocessing, hyperparameter optimization, and ensemble methods. You will build systems that classify documents, recognize images, detect ads, and more. You will learn to use scikit-learn’s API to extract features from categorical variables, text and images; evaluate model performance, and develop an intuition for how to improve your model’s performance.By the end of this book, you will master all required concepts of scikit-learn to build efficient models at work to carry out advanced tasks with the practical approach.

Mastering Machine Learning with Spark 2.x. Harness the potential of machine learning, through spark

Michal Malohlava, Alex Tellez, Max Pumperla

The purpose of machine learning is to build systems that learn from data. Being able to understand trends and patterns in complex data is critical to success; it is one of the key strategies to unlock growth in the challenging contemporary marketplace today. With the meteoric rise of machine learning, developers are now keen on finding out how can they make their Spark applications smarter. This book gives you access to transform data into actionable knowledge. The book commences by defining machine learning primitives by the MLlib and H2O libraries. You will learn how to use Binary classification to detect the Higgs Boson particle in the huge amount of data produced by CERN particle collider and classify daily health activities using ensemble Methods for Multi-Class Classification. Next, you will solve a typical regression problem involving flight delay predictions and write sophisticated Spark pipelines. You will analyze Twitter data with help of the doc2vec algorithm and K-means clustering. Finally, you will build different pattern mining models using MLlib, perform complex manipulation of DataFrames using Spark and Spark SQL, and deploy your app in a Spark streaming environment.