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Название: Blue Fox: ARM Assembly Internals and Reverse Engineering
Автор: Maria Markstedter
Издательство: Wiley
Год: 2023
Страниц: 476
Язык: английский
Формат: pdf (true)
Размер: 14.4 MB

Provides readers with a solid foundation in Arm assembly internals and reverse-engineering fundamentals as the basis for analyzing and securing billions of ARM devices. Finding and mitigating security vulnerabilities in ARM devices is the next critical internet security frontier—Arm processors are already in use by more than 90% of all mobile devices, billions of Internet of Things (IoT) devices, and a growing number of current laptops from companies including Microsoft, Lenovo, and Apple. Written by a leading expert on Arm security, Blue Fox: Arm Assembly Internals and Reverse Engineering introduces readers to modern Armv8-A instruction sets and the process of reverse-engineering ARM binaries for security research and defensive purposes. Divided into two sections, the book first provides an overview of the ELF file format and OS internals, followed by Arm architecture fundamentals, and a deep-dive into the A32 and A64 instruction sets. Section Two delves into the process of reverse-engineering itself: setting up an Arm environment, an introduction to static and dynamic analysis tools, and the process of extracting and emulating firmware for analysis. The last chapter provides the reader a glimpse into macOS malware analysis of binaries compiled for the Arm-based M1 SoC. Throughout the book, the reader is given an extensive understanding of Arm instructions and control-flow patterns essential for reverse engineering software compiled for the ARM architecture. Providing an in-depth introduction into reverse-engineering for engineers and security researchers alike, this book: Blue Fox: ARM Assembly Internals and Reverse Engineering is a vital resource for security researchers and reverse engineers who analyze software applications for ARM-based devices at the assembly level.

Название: Responsible Graph Neural Networks
Автор: Mohamed Abdel-Basset, Nour Moustafa, Hossam Hawash
Издательство: CRC Press
Год: 2023
Страниц: 324
Язык: английский
Формат: pdf (true)
Размер: 10.29 MB

More frequent and complex cyber threats require robust, automated, and rapid responses from cyber-security specialists. This book offers a complete study in the area of graph learning in cyber, emphasizing graph neural networks (GNNs) and their cyber-security applications. Three parts examine the basics, methods and practices, and advanced topics. The first part presents a grounding in graph data structures and graph embedding and gives a taxonomic view of GNNs and cyber-security applications. The second part explains three different categories of graph learning, including deterministic, generative, and reinforcement learning and how they can be used for developing cyber defense models. The discussion of each category covers the applicability of simple and complex graphs, scalability, representative algorithms, and technical details. To get you up and running for the hands-on learning experience, we need to set you up with an environment for running Python, Jupyter notebooks, the relevant libraries, and the code needed to run the book itself. The simplest way to get going will be to install Anaconda Framework. The Python 3.x version is required.

Название: From Data to Trade: A Machine Learning Approach to Quantitative Trading
Автор: Gautier Marti
Издательство: Independently published
Год: 2023
Язык: английский
Формат: pdf (true)
Размер: 14.2 MB

Machine Learning has revolutionized the field of quantitative trading, enabling traders to develop and implement sophisticated trading strategies that leverage large amounts of data and advanced modeling techniques. In this book, we provide a comprehensive overview of Machine Learning for quantitative trading, covering the fundamental concepts, techniques, and applications of Machine Learning in the financial industry. We start by introducing the key concepts and challenges of Machine Learning for quantitative trading, including feature engineering, model selection, and backtesting. We then delve into the various Machine Learning approaches that are commonly used in quantitative trading, including supervised learning, unsupervised learning, and reinforcement learning.

Название: Data Science Concepts and Techniques with Applications, 2nd Edition
Автор: Usman Qamar, Muhammad Summair Raza
Издательство: Springer
Год: 2023
Страниц: 492
Язык: английский
Формат: pdf
Размер: 13.3 MB

This textbook comprehensively covers both fundamental and advanced topics related to Data Science. Data Science is an umbrella term that encompasses data analytics, data mining, Machine Learning, and several other related disciplines. The chapters of this book are organized into three parts: The first part (chapters 1 to 3) is a general introduction to Data Science. Starting from the basic concepts, the book will highlight the types of data, its use, its importance and issues that are normally faced in data analytics, followed by presentation of a wide range of applications and widely used techniques in data science. The second part, which has been updated and considerably extended compared to the first edition, is devoted to various techniques and tools applied in Data Science. Its chapters 4 to 10 detail data pre-processing, classification, clustering, text mining, Deep Learning, frequent pattern mining, and regression analysis. Eventually, the third part (chapters 11 and 12) present a brief introduction to Python and R, the two main Data Science programming languages, and shows in a completely new chapter practical Data Science in the WEKA (Waikato Environment for Knowledge Analysis), an open-source tool for performing different Machine Learning and data mining tasks. An appendix explaining the basic mathematical concepts of Data Science completes the book.

Название: Data Structures with Python: Get familiar with the common Data Structures and Algorithms in Python
Автор: Dr. Harsh Bhasin
Издательство: BPB Publications
Год: 2023
Страниц: 404
Язык: английский
Формат: epub (true)
Размер: 10.2 MB

Develop a strong foundation in Data Structures and Algorithms and become a skilled programmer. Data structures are a way of organizing and storing data in a computer so that it can be accessed and manipulated efficiently. If you want to become an accomplished programmer and master this subject, then this book is for you. The book starts by introducing you to the fascinating world of data structures and algorithms. This book will help you learn about different algorithmic techniques such as Dynamic programming, Greedy algorithms, and Backtracking, and their applications in solving various computational problems. The book will then teach you how to analyze the complexity of Recursive algorithms. Moving on, the book will help you get familiar with the concept of Linked lists, which is an important foundation for understanding other data structures, such as Stacks and Queues, which are covered in detail later in this book. The book will also teach you about advanced data structures such as Trees and Graphs, their different types, and their applications. Towards the end, the book will teach you how to use various Sorting, Searching Selection and String algorithms.

Название: MultiSensor and MultiTemporal Remote Sensing
Автор: Anil Kumar, Priyadarshi Upadhyay, Uttara Singh
Издательство: CRC Press
Год: 2023
Страниц: 178
Язык: английский
Формат: pdf (true)
Размер: 10.2 MB

This book elaborates fuzzy Machine Learning and Deep Learning models for single class mapping from multi-sensor, multi-temporal remote sensing images while handling mixed pixels and noise. It also covers the ways of pre-processing and spectral dimensionality reduction of temporal data. Further, it discusses the ‘individual sample as mean’ training approach to handle heterogeneity within a class. The appendix section of the book includes case studies such as mapping crop type, forest species, and stubble burnt paddy fields. There are numerous Machine Learning models available for use in a variety of applications. Machine Learning classifers can fall into statistical categories such as c-Means, maximum-likelihood classifers, and decision-tree categories, such as random forest and Classifcation and Regression Tree (CART).

Название: Python for Everyone: Learn and polish your coding skills in Python
Автор: Saurabh Chandrakar, Dr. Nilesh Bhaskarrao Bahadure
Издательство: BPB Publications
Год: 2023
Страниц: 364
Язык: английский
Формат: pdf, epub (true)
Размер: 10.2 MB

A hands-on guide that will help you to write clean and efficient code in Python. Python is one of the most popular programming languages in the world, with a vast community of developers and users. In order to start using Python effectively, it is important to have a strong understanding of its core concepts. The purpose of this book is to introduce readers with little to no programming experience to Python and provide them with the foundational knowledge and skills necessary to begin writing code in the language. By mastering Python, readers will be able to apply this technology to solve real-world problems and create useful applications. This book covers a wide range of topics, from basic syntax and data types to more advanced concepts along with a little touch of Data Science. Overall, the book provides a solid foundation for beginners to start their journey for getting trained in Python language.

Название: Granular, Fuzzy, and Soft Computing: A Volume in the Encyclopedia of Complexity and Systems Science, Second Edition
Автор: Tsau-Young Lin, Churn-Jung Liau, Janusz Kacprzyk
Издательство: Springer
Год: 2023
Страниц: 936
Язык: английский
Формат: pdf (true)
Размер: 26.2 MB

For this volume of ECSS, Second Edition, many entries have been updated to capture these new developments, together with new chapters on such topics as data clustering, outliers in data mining, qualitative fuzzy sets, and information flow analysis for security applications. Granulations can be seen as a natural and ancient methodology deeply rooted in the human mind. Many daily "things" are routinely granulated into sub "things": The topography of earth is granulated into hills, plateaus, etc., space and time are granulated into infinitesimal granules, and a circle is granulated into polygons of infinitesimal sides. Such granules led to the invention of calculus, topology and non-standard analysis. Formalization of general granulation was difficult but, as shown in this volume, great progress has been made in combing discrete and continuous mathematics under one roof for a broad range of applications in Data Science. Soft computing was coined by Zadeh probably in the early 1980s to describe it as a consortium of the following areas: fuzzy logic (later augmented with rough sets), neural networks, and evolutionary computations. In fact, originally, probabilistic reasoning and Machine Learning were added, but this had not been followed as these areas concern different problems and use different tools and techniques.

Название: Deep Cognitive Networks: Enhance Deep Learning by Modeling Human Cognitive Mechanism
Автор: Yan Huang, Liang Wang
Издательство: Springer
Серия: SpringerBriefs in Computer Science
Год: 2023
Язык: английский
Формат: pdf (true), epub
Размер: 10.2 MB

Although Deep Learning models have achieved great progress in vision, speech, language, planning, control, and many other areas, there still exists a large performance gap between deep learning models and the human cognitive system. Many researchers argue that one of the major reasons accounting for the performance gap is that Deep Learning models and the human cognitive system process visual information in very different ways. To mimic the performance gap there has been a trend to model various cognitive mechanisms from cognitive neuroscience, e.g., attention, memory, reasoning, and decision, based on Deep Learning models. This book unifies these new kinds of Deep Learning models and calls them deep cognitive networks, which model various human cognitive mechanisms based on Deep Learning models. As a result, various cognitive functions are implemented, e.g., selective extraction, knowledge reuse, and problem solving, for more effective information processing.

Название: Artificial Intelligence for Students: A comprehensive overview of AI's foundation, applicability, and innovation
Автор: Vibha Pandey
Издательство: BPB Publications
Год: 2023
Страниц: 249
Язык: английский
Формат: epub (true)
Размер: 10.1 MB

A multifaceted approach to develop an understanding of AI and its potential applications. Artificial Intelligence (AI) is a discipline in Computer Science that focuses on developing intelligent machines, machines that can learn and then teach themselves. If you are interested in AI, this book can definitely help you prepare for future careers in AI and related fields. The book is aligned with the CBSE course, which focuses on developing employability and vocational competencies of students in skill subjects. The book is an introduction to the basics of AI. It is divided into three parts – AI-informed, AI-inquired and AI-innovate. It will help you understand AI's implications on society and the world. You will also develop a deeper understanding of how it works and how it can be used to solve complex real-world problems. Additionally, the book will also focus on important skills such as problem scoping, goal setting, data analysis, and visualization, which are essential for success in AI projects. Lastly, you will learn how decision trees, neural networks, and other AI concepts are commonly used in real-world applications.