Adversarial Tradecraft in Cybersecurity. Offense versus defense in real-time computer conflict

Dan Borges

Little has been written about what to do when live hackers are on your system and running amok. Even experienced hackers tend to choke up when they realize the network defender has caught them and is zoning in on their implants in real time. This book will provide tips and tricks all along the kill chain of an attack, showing where hackers can have the upper hand in a live conflict and how defenders can outsmart them in this adversarial game of computer cat and mouse.This book contains two subsections in each chapter, specifically focusing on the offensive and defensive teams. It begins by introducing you to adversarial operations and principles of computer conflict where you will explore the core principles of deception, humanity, economy, and more about human-on-human conflicts. Additionally, you will understand everything from planning to setting up infrastructure and tooling that both sides should have in place.Throughout this book, you will learn how to gain an advantage over opponents by disappearing from what they can detect. You will further understand how to blend in, uncover other actors’ motivations and means, and learn to tamper with them to hinder their ability to detect your presence. Finally, you will learn how to gain an advantage through advanced research and thoughtfully concluding an operation.By the end of this book, you will have achieved a solid understanding of cyberattacks from both an attacker’s and a defender’s perspective.

Learn Amazon SageMaker. A guide to building, training, and deploying machine learning models for developers and data scientists

Julien Simon, Francesco Pochetti

Amazon SageMaker enables you to quickly build, train, and deploy machine learning (ML) models at scale, without managing any infrastructure. It helps you focus on the ML problem at hand and deploy high-quality models by removing the heavy lifting typically involved in each step of the ML process. This book is a comprehensive guide for data scientists and ML developers who want to learn the ins and outs of Amazon SageMaker.You’ll understand how to use various modules of SageMaker as a single toolset to solve the challenges faced in ML. As you progress, you’ll cover features such as AutoML, built-in algorithms and frameworks, and the option for writing your own code and algorithms to build ML models. Later, the book will show you how to integrate Amazon SageMaker with popular deep learning libraries such as TensorFlow and PyTorch to increase the capabilities of existing models. You’ll also learn to get the models to production faster with minimum effort and at a lower cost. Finally, you’ll explore how to use Amazon SageMaker Debugger to analyze, detect, and highlight problems to understand the current model state and improve model accuracy.By the end of this Amazon book, you’ll be able to use Amazon SageMaker on the full spectrum of ML workflows, from experimentation, training, and monitoring to scaling, deployment, and automation.

Spark for Data Science. Click here to enter text

Srinivas Duvvuri, Bikramaditya Singhal

This is the era of Big Data. The words ‘Big Data’ implies big innovation and enables a competitive advantage for businesses. Apache Spark was designed to perform Big Data analytics at scale, and so Spark is equipped with the necessary algorithms and supports multiple programming languages.Whether you are a technologist, a data scientist, or a beginner to Big Data analytics, this book will provide you with all the skills necessary to perform statistical data analysis, data visualization, predictive modeling, and build scalable data products or solutions using Python, Scala, and R.With ample case studies and real-world examples, Spark for Data Science will help you ensure the successful execution of your data science projects.

Learning Grunt. Monitor and automate complex JavaScript tasks and processes by obtaining a practical understanding of Grunt

Douglas Reynolds

With the increasing focus on task automation, the Grunt task runner is a vast platform that allows you to incorporate automation into your workflows.At the outset, you will learn how to use Node.js and NMP through an example. You will then find out how to build a sample app and the development environment for it. You will further delve into the implementation of Grunt plugins and the configuration of Grunt tasks. Furthermore, you will explore the various methods and packages for workflow automation. The final chapter will cover some advanced concepts, such as configuration variables and how to create a Grunt plugin.By the end of the book, you will have gained the fundamentals of Grunt and progressed through advanced concepts, including building a Grunt plugin.

C++ Programming for Linux Systems. Create robust enterprise software for Linux and Unix-based operating systems

Desislav Andreev, Stanimir Lukanov, Milena Lazarova

Around 35 million Linux and almost 2 billion Android users rely on C++ for everything from the simplest embedded and IoT devices to cloud services, supercomputing, and space exploration. To help you produce high-quality software, two industry experts have transformed their knowledge and experience into practical examples in system programming with C++ Programming for Linux Systems.In this book, you'll explore the latest C++20 features, while working on multiple specific use cases. You’ll get familiar with the coroutines and modern approaches in concurrent and multithreaded programming. You'll also learn to reshape your thinking when analyzing system behavior in Linux (POSIX) environments. Additionally, you'll discover advanced discussions and novel solutions for complex challenges, while approaching trivial system operations with a new outlook and learning to choose the best design for your particular case.You can use this workbook as an introduction to system programming and software design in Linux or any Unix-based environment. You’ll also find it useful as a guideline or a supplement to any C++ book.By the end of this book, you’ll have gained advanced knowledge and skills for working with Linux or any Unix-based environment.

The Unsupervised Learning Workshop. Get started with unsupervised learning algorithms and simplify your unorganized data to help make future predictions

Aaron Jones, Christopher Kruger, Benjamin Johnston

Do you find it difficult to understand how popular companies like WhatsApp and Amazon find valuable insights from large amounts of unorganized data? The Unsupervised Learning Workshop will give you the confidence to deal with cluttered and unlabeled datasets, using unsupervised algorithms in an easy and interactive manner.The book starts by introducing the most popular clustering algorithms of unsupervised learning. You'll find out how hierarchical clustering differs from k-means, along with understanding how to apply DBSCAN to highly complex and noisy data. Moving ahead, you'll use autoencoders for efficient data encoding.As you progress, you’ll use t-SNE models to extract high-dimensional information into a lower dimension for better visualization, in addition to working with topic modeling for implementing natural language processing (NLP). In later chapters, you’ll find key relationships between customers and businesses using Market Basket Analysis, before going on to use Hotspot Analysis for estimating the population density of an area.By the end of this book, you’ll be equipped with the skills you need to apply unsupervised algorithms on cluttered datasets to find useful patterns and insights.

Interpretable Machine Learning with Python. Build explainable, fair, and robust high-performance models with hands-on, real-world examples - Second Edition

Serg Masís, Aleksander Molak, Denis Rothman

Interpretable Machine Learning with Python, Second Edition, brings to light the key concepts of interpreting machine learning models by analyzing real-world data, providing you with a wide range of skills and tools to decipher the results of even the most complex models.Build your interpretability toolkit with several use cases, from flight delay prediction to waste classification to COMPAS risk assessment scores. This book is full of useful techniques, introducing them to the right use case. Learn traditional methods, such as feature importance and partial dependence plots to integrated gradients for NLP interpretations and gradient-based attribution methods, such as saliency maps.In addition to the step-by-step code, you’ll get hands-on with tuning models and training data for interpretability by reducing complexity, mitigating bias, placing guardrails, and enhancing reliability.By the end of the book, you’ll be confident in tackling interpretability challenges with black-box models using tabular, language, image, and time series data.

AWS SysOps Cookbook. Practical recipes to build, automate, and manage your AWS-based cloud environments - Second Edition

Eric Z. Beard, Rowan Udell, Lucas Chan

AWS is an on-demand remote computing service providing cloud infrastructure over the internet with storage, bandwidth, and customized support for APIs. This updated second edition will help you implement these services and efficiently administer your AWS environment.You will start with the AWS fundamentals and then understand how to manage multiple accounts before setting up consolidated billing. The book will assist you in setting up reliable and fast hosting for static websites, sharing data between running instances and backing up data for compliance. By understanding how to use compute service, you will also discover how to achieve quick and consistent instance provisioning. You’ll then learn to provision storage volumes and autoscale an app server. Next, you’ll explore serverless development with AWS Lambda, and gain insights into using networking and database services such as Amazon Neptune. The later chapters will focus on management tools like AWS CloudFormation, and how to secure your cloud resources and estimate costs for your infrastructure. Finally, you’ll use the AWS well-architected framework to conduct a technology baseline review self-assessment and identify critical areas for improvement in the management and operation of your cloud-based workloads.By the end of this book, you’ll have the skills to effectively administer your AWS environment.