Professional and Applied Computing

• Acquire and investigate data from mobile devices using forensically sound, industry-standard tools
  
• Understand the relationship between mobile and desktop devices in criminal and corporate investigations
  
• Analyze backup files and artifacts for forensic evidence

Learn how to use the Processing programming language and environment to create Android applications with ease. This book covers the basics of the Processing language, allowing users to effectively program interactive graphics in 2D, 3D, and Extended Reality (XR). It also details the application of these techniques to different types of Android devices (smartphones, tablets, wearables, and smartwatches). 

This updated edition walks you through the entire process of creating an app, from the initial idea to release of the final app via the Google Play App Store. Over the course of the book, you’ll learn to write engaging apps driven by user interaction and sensor data. A comprehensive series of hands-on projects, ranging from simple sketches to more complex projects involving shaders, VR, and AR will give you the firsthand experience you need to begin developing your own projects.

And once you have your Processing projects completed, you’ll be able to upload them to the Google Play store to be shared with the world!

What You Will Learn

• Write apps and live wallpapers for smartphones and tablets
• Design and implement interactive watch faces
• Create Extended Reality (VR/AR) experiences
• Incorporate GLSL shaders into your Processing apps
• Integrate Processing sketches into larger apps and Android Studio
• Learn how to write your own libraries to share with the community
• Export projects as completed apps ready to distribute through Google Play Store

Who This Book Is For

In the ever-evolving world of cybersecurity, the need for robust and proactive threat intelligence has never been more critical. This book is designed to arm you with the essential knowledge and tools required to establish a world-class cyber threat intelligence (CTI) capability. Authored by Crawford Thomas, a seasoned expert with over two decades of frontline experience in military intelligence and cyber threat intelligence within the financial sector, this guide is not just theoretical—it's a distillation of hard-earned, practical wisdom.

This book is not a typical consultation manual filled with checkboxes and generic advice. Instead, it draws from the real-world experiences of a practitioner who has navigated the complexities of regulatory pressures and excelled in environments that demand nothing less than excellence. Notably, during a recent CBEST testing, Thomas’s leadership and the performance of his CTI team were described as "formidable." This recognition underscores the level of expertise and effectiveness you can expect to learn from.

You are invited on a comprehensive journey through the critical stages of building a CTI function: from developing a strategic vision, formulating prioritized intelligence requirements, and selecting the right vendors, to mastering the nuances of intelligence reporting. This book is designed to guide you in creating a CTI capability that not only protects your business, but also enhances its efficacy and fosters an environment of reliability and trust—both internally and externally.

The necessity for this book stems from the current cybersecurity landscape where businesses face an increasing barrage of threats. They require impeccable IT security across all platforms, often taking on risks that stretch beyond their risk appetite. Email systems, provided ubiquitously by major vendors, remain a prime target despite advanced security measures. Meanwhile, the rise of Ransomware as a Service has given a new edge to this already formidable threat, turning organizations into unwitting participants in attacks aimed at third-party applications.

What You Will Learn:

• How to build a world leading cyber threat intelligence capability that is threat vector focused.


• Estimate the size of the cyber threat intelligence team you require,


• How to build the prioritized intelligence requirements (PIRs) and collection plan.


• How to select the correct cyber security vendor—in line with the PIRs.


• How to develop ‘pull intelligence’ production and reporting writing.

Who This Book is for:

This book is for all levels of cyber analyst capability. From the beginner, with a hunger to find a definitive answer to ‘what is a cyber threat intelligence capability’? To the expert, who is keen to learn of a better way to do their tradecraft. this book is also for the frustrated and burnt out in-house cyber specialist, who has grown cautious of the vendor market, the costs, the lack of integrations. The 10 year cyber expert who is aware of the changing threat landscape and the need to be more dynamic, responsive and efficient.

Generative AI and Agentic AI together are revolutionizing the technology landscape, with profound and far-reaching impacts across industries. Organizations are increasingly adopting these technologies to drive innovation, enhance unstructured content management, and improve problem-solving capabilities. With Agentic AI, enterprises are moving towards the development of intelligent systems that can plan, reason, and act with autonomy. While early proof-of-concepts (POCs) demonstrated the potential of these technologies, the current shift is toward responsible and scalable production implementations that leverage both generative and agentic capabilities.
This book begins by guiding you through the technological evolution of AI, from early machine learning to today’s large language models (LLMs) and agentic systems. It then explores a wide range of use cases across industries, highlighting how LLMs can support decision-making, and how Agentic AI enables dynamic, collaborative systems that act with autonomy and intent. This is followed by Design Patterns across the lifecycle of AI solution development, deployment and monitoring. Readers will then gain insights into the methodologies for developing and deploying Generative and Agentic AI solutions at an enterprise level. A featured implementation demonstrates how Agentic AI can be effectively put into action.
The book also introduces essential concepts such as MLOps, LLMOps, and Responsible AI principles which are critical for transitioning the AI solutions from experimentation to production. These principles ensure that AI deployments are scalable, secure, ethical and compliant. The book concludes with key takeaways and best practices for developing, evaluating, deploying and scaling AI applications responsibly and effectively within enterprise settings.

You Will:

• Understand key design patterns to develop, deploy and monitor a Generative AI solution effectively.
• Learn how to develop and implement a production-ready Agentic AI use case.
• Discover best practices for building scalable, secure, and enterprise-grade AI solutions.
• Understand how to assess and mitigate risks using Responsible AI principles and LLMOps best practices.

This book is for : Enterprise Software Engineers and Architects

This books helps you embark on the journey to master the art of Appium automation, from installation all the way to building a Plugin and Driver. It covers the Appium 3.0 version which is the latest version which involves a complete re-architecture. 

You'll begin by following step-by-step instructions on installing Appium, configuring Node packages, and creating a simple test. In these initial chapters, you'll gain an understanding of Appium Architecture and the command lifecycle. Once you understand the basics, the book will then guide you in testing automation for Android and iOS, both for real devices and for emulators. These chapters also provide instructions on how to run tests in parallel, native shell commands, and how to prepare iOS real devices for test automation. Chapters also cover low-level technical implementations, which will enable you to contribute to Appium and open a way to open-source software contributions.

Following this, you'll discuss the intricacies of configuring and developing robust method wrappers, a crucial skill for supporting multiple test suites with both native commands. The book goes beyond the basics, exploring techniques to make test suites faster when running tests in CI like Jenkins, GitHub Actions, as well as cloud environments like Lambda Test, BrowserStack. It will also help you understand advanced topics such as gestures, plugin development, and continuous testing in CI environments.

By the end of this book, you'll have developed the expertise to debug Appium command failures and construct a sophisticated test automation framework, as well as excel in your Appium test automation endeavours and deliver reliable, efficient testing solutions.

What You'll Learn:

• Master advanced techniques in Appium Mobile Test Automation.
• Solve common challenges encountered in real-world projects and strategize to overcome them.
• Test automation for various platforms like TV apps, Roku, Raspberry Pi, and more.
• Contribute to the Appium project and engage in open-source contributions.

Who is this book for:

Software Testers, software architects, QA engineers, and DevOps engineers

AI will fundamentally change the way business is conducted across most industries. Organizations that excel at leveraging secure, responsible AI to advance their strategic objectives will have a distinct advantage. Those that do not may see their market share erode.

This book provides a guide for organizations to integrate AI in alignment with the organization's strategic goals. The framework provides a roadmap for adopting secure, responsible, and resilient AI, from initial strategy development to ongoing operations that will help advance market leadership.

Part one of the book discusses laying a solid foundation to ensure successful AI integration, beginning with developing an AI strategy aligned with strategic business objectives, such as product and service differentiation, market expansion, and process optimization.

Part Two takes a deep dive into ensuring secure and safe AI adoption. It proposes a secure-by-design approach to AI development that considers AI-specific attack vectors and associated security practices throughout the AI lifecycle.

Developing and deploying secure, responsible, and resilient AI is not a one-time effort. Therefore, Part Three discusses operationalizing AI and integrating it throughout the enterprise to ensure continued success. This section focuses on scaling AI applications and continuous improvement, including establishing metrics and conducting a post-deployment ROI evaluation. Finally, it discusses how to foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business.

What You Will Learn:

• Develop an AI integration strategy aligned with the organization's strategic goals and objectives.
• Incorporate a secure-by-design approach to AI integration that considers AI-specific attack vectors and applies traditional and AI-specific defense methods, such as adversarial development, model behavior monitoring, drift analysis, input validation and filtering, and output filtering.
• Establish an AI governance and risk management framework to ensure ongoing compliance with applicable legislation, industry standards, organizational policies, and responsible AI principles.
• Operationalize and scale AI applications to ensure resilient production usage and facilitate continuous improvement.
• Foster a culture of AI innovation and excellence, ensuring that AI becomes a way of doing business.

Who This Book is for:

The primary audience includes business leaders, AI practitioners, AI executives, AI governance professionals, and cybersecurity leaders looking to integrate AI as a strategic differentiator and to enhance business operations. Higher education would be a secondary audience.