IDS and IPS with Snort 3. Get up and running with Snort 3 and discover effective solutions to your security issues

Ashley Thomas

Snort, an open source intrusion detection and prevention system (IDS/IPS), capable of real-time traffic analysis and packet logging, is regarded as the gold standard in IDS and IPS. The new version, Snort 3, is a major upgrade to the Snort IDS/IPS, featuring a new design and enhanced detection functionality, resulting in higher efficacy and improved performance, scalability, usability, and extensibility. Snort 3 is the latest version of Snort, with the current version at the time of writing being Snort v3.3.3.This book will help you understand the fundamentals of packet inspection in Snort and familiarize you with the various components of Snort. The chapters take you through the installation and configuration of Snort, focusing on helping you fine-tune your installation to optimize Snort performance. You’ll get to grips with creating and modifying Snort rules, fine-tuning specific modules, deploying and configuring, as well as troubleshooting Snort. The examples in this book enable network administrators to understand the real-world application of Snort, while familiarizing them with the functionality and configuration aspects.By the end of this book, you’ll be well-equipped to leverage Snort to improve the security posture of even the largest and most complex networks.

Et al. Because not all research deserves a Nobel Prize

B McGraw

Tired of the same old math, science, statistics, and programming memes people post online and want something a little more elaborate? This is the book for you.Tremble as we make up all our own facts and data, hand-draw diagrams in MS Paint, and quote from fictional studies and journals. Cower as authors write in the first person because their study is just a little too personal for them. Recoil from the sheer mass of oversimplified methodology, distilling someone's entire thesis into a paragraph of jokes crude enough to make it into a Mike Myers movie.Over the last few years, we have taken arguments that you would normally have after four Jack and cokes at game night and turned them into properly formatted research papers with a writing tone serious enough to confuse the uninitiated. These papers are high-effort jokes by researchers and scientists for researchers and scientists. They cover a range of topics such as the consequences of re-releasing tourists back into Yellowstone National Park after COVID-19, how to play StarCraft competitively online on a quantum computer, and most importantly, how trees around the globe are becoming increasingly radicalized.

Artificial Intelligence Engines. A Tutorial Introduction to the Mathematics of Deep Learning

James V Stone

This book is a comprehensive guide to the mathematics behind artificial intelligence engines, taking readers from foundational concepts to advanced applications. It begins with an introduction to artificial neural networks, exploring topics like perceptrons, linear associative networks, and gradient descent. Practical examples accompany each chapter, making complex mathematical principles accessible, even for those with limited prior knowledge.The book's detailed structure covers key algorithms like backpropagation, Hopfield networks, and Boltzmann machines, advancing to deep restricted Boltzmann machines, variational autoencoders, and convolutional neural networks. Modern topics such as generative adversarial networks, reinforcement learning, and capsule networks are explored in depth. Each section connects theory to real-world AI applications, helping readers understand how these techniques are used in practice.Ideal for students, researchers, and AI enthusiasts, the book balances theoretical depth with practical insights. Basic mathematical knowledge or foundation is recommended, allowing readers to fully engage with the content. This book serves as an accessible yet thorough resource for anyone eager to dive deeper into artificial intelligence and machine learning.

The Complete Guide to Defense in Depth. Learn to identify, mitigate, and prevent cyber threats with a dynamic, layered defense approach

Akash Mukherjee, Jason D. Clinton

In an era of relentless cyber threats, organizations face daunting challenges in fortifying their defenses against increasingly sophisticated attacks. The Complete Guide to Defense in Depth offers a comprehensive roadmap to navigating the complex landscape, empowering you to master the art of layered security.This book starts by laying the groundwork, delving into risk navigation, asset classification, and threat identification, helping you establish a robust framework for layered security. It gradually transforms you into an adept strategist, providing insights into the attacker's mindset, revealing vulnerabilities from an adversarial perspective, and guiding the creation of a proactive defense strategy through meticulous mapping of attack vectors. Toward the end, the book addresses the ever-evolving threat landscape, exploring emerging dangers and emphasizing the crucial human factor in security awareness and training. This book also illustrates how Defense in Depth serves as a dynamic, adaptable approach to cybersecurity.By the end of this book, you’ll have gained a profound understanding of the significance of multi-layered defense strategies, explored frameworks for building robust security programs, and developed the ability to navigate the evolving threat landscape with resilience and agility.

Machine Learning in Microservices. Productionizing microservices architecture for machine learning solutions

Mohamed Abouahmed, Omar Ahmed

With the rising need for agile development and very short time-to-market system deployments, incorporating machine learning algorithms into decoupled fine-grained microservices systems provides the perfect technology mix for modern systems. Machine Learning in Microservices is your essential guide to staying ahead of the curve in this ever-evolving world of technology.The book starts by introducing you to the concept of machine learning microservices architecture (MSA) and comparing MSA with service-based and event-driven architectures, along with how to transition into MSA. Next, you’ll learn about the different approaches to building MSA and find out how to overcome common practical challenges faced in MSA design. As you advance, you’ll get to grips with machine learning (ML) concepts and see how they can help better design and run MSA systems. Finally, the book will take you through practical examples and open source applications that will help you build and run highly efficient, agile microservices systems.By the end of this microservices book, you’ll have a clear idea of different models of microservices architecture and machine learning and be able to combine both technologies to deliver a flexible and highly scalable enterprise system.

Instant Optimizing Embedded Systems Using BusyBox. Learn to optimize embedded systems with Busybox using practical, hands-on recipes

Wu Zhangjin, Cao Ziqiang

As hundreds of millions of people have started using Android smartphones, embedded Linux systems are becoming more and more popular. To get more market share, not only for hardware and function piling up, smartphone manufacturers gradually realized the importance of user experience. To improve user experience, the back-end Linux system must be optimized in many ways.Instant Optimizing Embedded System Using BusyBox is a practical, hands-on guide that provides you with a number of clear, step-by-step exercises to help you take advantage of the real power behind Busybox, and give you a good grounding for using it to optimize your embedded (Android Linux) systems.Moving on from the basics, this book will teach you how to configure and compile it from source code, including cross-compiling it with static linking and dynamic linking. You will also learn how to install and use Busybox on the Android emulator. You will learn to replace the simple Android mksh console with Busybox ash console and start a telnet and HTTP service provided by Busybox. You will also build embedded Linux file system from scratch and start it on Android emulator. We will take a look at how to add functionality to Busybox based system, including adding external applets to Busybox, as well as building development environments (like Bash and C) for it manually or with the automatic Buildroot system.If want to learn how to take advantage of using Busybox applets to optimize your embedded system, then this is the book for you for it will also show you how to use the powerful applets to optimize multiple aspects of an embedded (Android Linux) system.This book will teach you how to build an embedded (Android Linux) system with Busybox, enhance its functionality to meet diverse system requirements, and optimize it to provide a better user experience for embedded products.

Dancing with Python. Learn to code with Python and Quantum Computing

Robert S. Sutor

Dancing with Python helps you learn Python and quantum computing in a practical way. It will help you explore how to work with numbers, strings, collections, iterators, and files.The book goes beyond functions and classes and teaches you to use Python and Qiskit to create gates and circuits for classical and quantum computing. Learn how quantum extends traditional techniques using the Grover Search Algorithm and the code that implements it. Dive into some advanced and widely used applications of Python and revisit strings with more sophisticated tools, such as regular expressions and basic natural language processing (NLP). The final chapters introduce you to data analysis, visualizations, and supervised and unsupervised machine learning.By the end of the book, you will be proficient in programming the latest and most powerful quantum computers, the Pythonic way.

Generative Deep Learning with Python. Unleashing the Creative Power of AI by Mastering AI and Python

Cuantum Technologies LLC

Generative Deep Learning with Python opens the door to the fascinating world of AI where machines create. This course begins with an introduction to deep learning, establishing the essential concepts and techniques. You will then delve into generative models, exploring their theoretical foundations and practical applications. As you progress, you will gain a deep understanding of Generative Adversarial Networks (GANs), learning how they function and how to implement them for tasks like face generation.The course's hands-on projects, such as creating GANs for face generation and using Variational Autoencoders (VAEs) for handwritten digit generation, provide practical experience that reinforces your learning. You'll also explore autoregressive models for text generation, allowing you to see the versatility of generative models across different types of data. Advanced topics will prepare you for cutting-edge developments in the field.Throughout your journey, you will gain insights into the future landscape of generative deep learning, equipping you with the skills to innovate and lead in this rapidly evolving field. By the end of the course, you will have a solid foundation in generative deep learning and be ready to apply these techniques to real-world challenges, driving advancements in AI and machine learning.