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Cluster analysis. --- Fuzzy algorithms. --- Pattern perception.

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"The use of metaheuristic algorithms (MA) has been increasing in recent years, and the image processing field is not the exempted of their application. In the last two years a big amount of MA have been introduced as alternatives for solving complex optimization problems. This book collects the most prominent MA of the 2019 and 2020 and verifies its use in image processing tasks. In addition, literature review of both MA and digital image processing is presented as part of the introductory information. Each algorithm is detailed explained with special focus in the tuning parameters and the proper implementation for the image processing tasks. Besides several examples permits to the reader explore and confirm the use of this kind of intelligent methods. Since image processing is widely used in different domains, this book considers different kinds of datasets that includes, magnetic resonance images, thermal images, agriculture images, among others. The reader then can have some ideas of implementation that complement the theory exposed of each optimization mechanism. Regarding the image processing problems this book consider the segmentation by using different metrics based on entropies or variances. In the same way, the identification of different shapes and the detection of objects are also covered in the corresponding chapters. Each chapter is complemented with a wide range of experiments and statistical analysis that permits the reader to judge about the performance of the MA. Finally, there is included a section that includes some discussion and conclusions. This section also provides some open questions and research opportunities for the audience"--

Fuzzy algorithms. --- Metaheuristics. --- Image processing --- Digital techniques.

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Fuzzy algorithms. --- Image processing --- Pattern recognition systems. --- Digital techniques.

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Find security flaws in any architecture effectively through emulation and fuzzing with QEMU and AFL Purchase of the print or Kindle book includes a free PDF eBook Key Features Understand the vulnerability landscape and useful tools such as QEMU and AFL Explore use cases to find vulnerabilities and execute unknown firmware Create your own firmware emulation and fuzzing environment to discover vulnerabilities Book Description Emulation and fuzzing are among the many techniques that can be used to improve cybersecurity; however, utilizing these efficiently can be tricky. Fuzzing Against the Machine is your hands-on guide to understanding how these powerful tools and techniques work. Using a variety of real-world use cases and practical examples, this book helps you grasp the fundamental concepts of fuzzing and emulation along with advanced vulnerability research, providing you with the tools and skills needed to find security flaws in your software. The book begins by introducing you to two open source fuzzer engines: QEMU, which allows you to run software for whatever architecture you can think of, and American fuzzy lop (AFL) and its improved version AFL++. You'll learn to combine these powerful tools to create your own emulation and fuzzing environment and then use it to discover vulnerabilities in various systems, such as iOS, Android, and Samsung's Mobile Baseband software, Shannon. After reading the introductions and setting up your environment, you'll be able to dive into whichever chapter you want, although the topics gradually become more advanced as the book progresses. By the end of this book, you'll have gained the skills, knowledge, and practice required to find flaws in any firmware by emulating and fuzzing it with QEMU and several fuzzing engines. What you will learn Understand the difference between emulation and virtualization Discover the importance of emulation and fuzzing in cybersecurity Get to grips with fuzzing an entire operating system Discover how to inject a fuzzer into proprietary firmware Know the difference between static and dynamic fuzzing Look into combining QEMU with AFL and AFL++ Explore Fuzz peripherals such as modems Find out how to identify vulnerabilities in OpenWrt Who this book is for This book is for security researchers, security professionals, embedded firmware engineers, and embedded software professionals. Learners interested in emulation, as well as software engineers interested in vulnerability research and exploitation, software testing, and embedded software development will also find it useful. The book assumes basic knowledge of programming (C and Python); operating systems (Linux and macOS); and the use of Linux shell, compilation, and debugging.

Internet of things --- Fuzzy algorithms. --- Security measures --- Research --- Methodology.

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Intelligent control systems. --- Fuzzy algorithms. --- Artificial intelligence. --- Commande intelligente --- Intelligence artificielle