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Kumar Chetan Sharma, Stoyan Stefanov, Ved Antani, Gaston C. Hillar
JavaScript is the behavior, the third pillar in today's paradigm that looks at web pages as something that consists of : content (HTML), presentation (CSS), and behavior (JavaScript). Using JavaScript, you can create interactive web pages along with desktop widgets, browser, and application extensions, and other pieces of software. Object-oriented programming, which is popularly known as OOP, is basically based on the concept of objects rather than actions. The first module will help you master JavaScript and build futuristic web applications. You will start by getting acquainted with the language constructs and how to organize code easily. You develop concrete understanding of variable scoping, loops, and best practices on using types and data structures, as well as the coding style and recommended code organization patterns in JavaScript. The book will also teach you how to use arrays and objects as data structures. By the end of the book, you will understand how reactive JavaScript is going to be the new paradigm.The second module is an easy-to-follow course, which includes hands-on examples of solutions to common problems with object-oriented code. It will help to identify objects from real-life scenarios, to protect and hide data with the data encapsulation features of Python, JavaScript, and C#. You will discover the advantage of duck typing in both Python and JavaScript, while you work with interfaces and generics in C#. With a fair understanding of interfaces, multiple inheritance, and composition, you will move on to refactor existing code and to organize your source for easy maintenance and extension.The third module takes you through all the in-depth and exciting futures hidden behind the facade. You should read through this course if you want to be able to take your JavaScript skills to a new level of sophistication.
NSA Security-Enhanced Linux (SELinux) is a set of patches and added utilities to the Linux kernel to incorporate a strong, flexible, mandatory access control architecture into the major subsystems of the kernel. With its fine-grained yet flexible approach, it is no wonder Linux distributions are firing up SELinux as a default security measure.SELinux System Administration covers the majority of SELinux features through a mix of real-life scenarios, descriptions, and examples. Everything an administrator needs to further tune SELinux to suit their needs are present in this book.This book touches on various SELinux topics, guiding you through the configuration of SELinux contexts, definitions, and the assignment of SELinux roles, and finishes up with policy enhancements. All of SELinux's configuration handles, be they conditional policies, constraints, policy types, or audit capabilities, are covered in this book with genuine examples that administrators might come across.By the end, SELinux System Administration will have taught you how to configure your Linux system to be more secure, powered by a formidable mandatory access control.
Adversarial attacks trick AI systems with malicious data, creating new security risks by exploiting how AI learns. This challenges cybersecurity as it forces us to defend against a whole new kind of threat. This book demystifies adversarial attacks and equips you with the skills to secure AI technologies, moving beyond research hype or business-as-usual activities. Learn how to defend AI and LLM systems against manipulation and intrusion through adversarial attacks such as poisoning, trojan horses, and model extraction, leveraging DevSecOps, MLOps, and other methods to secure systems.This strategy-based book is a comprehensive guide to AI security, combining structured frameworks with practical examples to help you identify and counter adversarial attacks. Part 1 introduces the foundations of AI and adversarial attacks. Parts 2, 3, and 4 cover key attack types, showing how each is performed and how to defend against them. Part 5 presents secure-by-design AI strategies, including threat modeling, MLSecOps, and guidance aligned with OWASP and NIST. The book concludes with a blueprint for maturing enterprise AI security based on NIST pillars, addressing ethics and safety under Trustworthy AI.By the end of this book, you’ll be able to develop, deploy, and secure AI systems against the threat of adversarial attacks effectively.
For beginners and experienced IT risk professionals alike, acing the ISACA CRISC exam is no mean feat, and the application of this advanced skillset in your daily work poses a challenge. The ISACA Certified in Risk and Information Systems Control (CRISC®) Certification Guide is a comprehensive guide to CRISC certification and beyond that’ll help you to approach these daunting challenges with its step-by-step coverage of all aspects of the exam content and develop a highly sought-after skillset in the process.This book is divided into six sections, with each section equipped with everything you need to get to grips with the domains covered in the exam. There’ll be no surprises on exam day – from GRC to ethical risk management, third-party security concerns to the ins and outs of control design, and IDS/IPS to the SDLC, no stone is left unturned in this book’s systematic design covering all the topics so that you can sit for the exam with confidence. What’s more, there are chapter-end self-assessment questions for you to test all that you’ve learned, as well as two book-end practice quizzes to really give you a leg up.By the end of this CRISC exam study guide, you’ll not just have what it takes to breeze through the certification process, but will also be equipped with an invaluable resource to accompany you on your career path.
Data engineering provides the foundation for data science and analytics, and forms an important part of all businesses. This book will help you to explore various tools and methods that are used for understanding the data engineering process using Python.The book will show you how to tackle challenges commonly faced in different aspects of data engineering. You’ll start with an introduction to the basics of data engineering, along with the technologies and frameworks required to build data pipelines to work with large datasets. You’ll learn how to transform and clean data and perform analytics to get the most out of your data. As you advance, you'll discover how to work with big data of varying complexity and production databases, and build data pipelines. Using real-world examples, you’ll build architectures on which you’ll learn how to deploy data pipelines.By the end of this Python book, you’ll have gained a clear understanding of data modeling techniques, and will be able to confidently build data engineering pipelines for tracking data, running quality checks, and making necessary changes in production.