Название: Zero Trust Networks: Building Secure Systems in Untrusted Networks, 2nd Edition (Final)
Автор: Razi Rais, Christina Morillo, Evan Gilman
Издательство: O’Reilly Media, Inc.
Год: 2024
Страниц: 332
Язык: английский
Формат: pdf, epub (true)
Размер: 15.6 MB

This practical book provides a detailed explanation of the zero trust security model. Zero trust is a security paradigm shift that eliminates the concept of traditional perimeter-based security and requires you to "always assume breach" and "never trust but always verify." The updated edition offers more scenarios, real-world examples, and in-depth explanations of key concepts to help you fully comprehend the zero trust security architecture. Zero trust aims to solve the inherent problems in placing our trust in the network. Instead, it is possible to secure network communication and access so effectively that the physical security of the transport layer can be reasonably disregarded. It goes without saying that this is a lofty goal. The good news is that we’ve got pretty powerful cryptographic algorithms these days, and given the right automation systems, this vision is actually attainable. For network engineers, security engineers, CTOs, and everyone in between can benefit from zero trust learnings. Even without a specialized skill set, many of the principles included in this book can be clearly understood, helping leaders make decisions that implement a zero trust model, improving their overall security posture incrementally.

Название: Introduction to Cybersecurity in the Internet of Things
Автор: Keke Gai, Jing Yu, Liehuang Zhu
Издательство: CRC Press
Год: 2024
Страниц: 645
Язык: английский
Формат: pdf (true)
Размер: 16.7 MB

This book addresses the security challenges facing the rapidly growing Internet of Things (IoT) industry, including the potential threats and risks arising from its complex architecture. The authors discuss the overall IoT architecture, covering networking, computing, and security threats and risks to hardware such as sensors, actuators, and portable devices, as well as infrastructure layers. They cover a range of technical concepts such as cryptography, distributed storage, and data transmission, and offer practical advice on implementing security solutions such as authentication and access control. By exploring the future of cybersecurity in the IoT industry, with insights into the importance of big data and the threats posed by data mining techniques, this book is an essential resource for anyone interested in, or working in, the rapidly evolving field of IoT security. The main content in this book is formed by four parts. The first part provides learners with basic information about cybersecurity in mobile computing from three perspectives, including basic concepts, fundamental cyber issues in mobile computing, and relevant knowledge about the Internet-of-Things (IoT) and cloud computing.

Название: Low-Power Wide Area Network for Large Scale Internet of Things: Architectures, Communication ­Protocols and Recent Trends
Автор: Mariyam Ouaissa, Mariya Ouaissa, Inam Ullah Khan, Zakaria Boulouard
Издательство: CRC Press
Серия: Prospects in Networking and Communication
Год: 2024
Страниц: 275
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

This book presents a comprehensive exploration of LPWANs, delving into their fundamental concepts, underlying technologies, and the multifaceted challenges they tackle. This book recognizes that LPWANs don't operate in isolation; they are intimately intertwined with Artificial Intelligence and Machine Learning (AI/ML) technologies, which play a pivotal role in optimizing LPWAN performance and capabilities. The book is a collection of original contributions regarding air interface, transmission technologies and novel network architectures, such as network slicing, cloud/fog/edge computing, ad hoc networks and software-defined network. Also, this book provides a guide for researchers of IoT applications to choose suitable LPWAN technologies and describe the design aspects, network architectures, security issues and challenges.

Название: Home Networking Tricks and Tips - 3rd Edition 2024
Автор: Papercut Limited
Издательство: Papercut Limited
Год: 2024
Язык: английский
Формат: pdf
Размер: 41.3 MB

"Home Networking Tricks and Tips" - это безупречное цифровое издание для пользователей, которые желают поднять свои знания и навыки на новый уровень. Хотите ли вы улучшить свои пользовательские навыки или получить новые знания? Хотите ли вы учиться напрямую у экспертов в этой области? Хотите ли вы изучить многие приемы, которые используют профессионалы? На этих страницах для продвинутых пользователей вы узнаете все, что вам нужно знать, чтобы стать более уверенным, компетентным и опытным пользователем. Пользователем, который способен получить максимальную отдачу от своего устройства, а значит, и от "умного дома" в целом. Мы поддерживаем и обучаем вас навыкам, приобретенным за десятилетия опыта, с учетом ваших пожеланий.

Название: Информационная безопасность и защита информации
Автор: Прохорова О.В.
Издательство: СГАСУ
Год: 2014
Cтраниц: 112
Формат: pdf
Размер: 25 мб
Язык: русский

Учебник по курсу «Информационная безопасность и защита информации» для студентов 2 курса специальности 230400.62 «Информационные системы и технологии». В учебнике рассматриваются основы информационной безопасности и защиты информации, а именно: разграничение доступа к ресурсам, вопросы идентификации и аутентификации субъектов, методы и средства криптографической защиты, вопросы контроля целостности информации, способы хранения и распределения ключевой информации, организация защиты информации от разрушающих программных воздействий, электронно-цифровая подпись и многое другое.

Название: The AI Revolution in Networking, Cybersecurity, and Emerging Technologies (Final)
Автор: Omar Santos, Samer Salam, Hazim Dahir
Издательство: Addison-Wesley Professional/Pearson Education
Год: 2024
Страниц: 221
Язык: английский
Формат: pdf (true), epub (true)
Размер: 10.6 MB

The AI Revolution is Here. Discover its Dynamic Applications in Networking, Cybersecurity, and More. AI is having a profound impact on nearly every sector of the workforce. Huge professional and financial opportunities await in the key domains of computer networking, cybersecurity, IoT, and cloud computing. The AI Revolution in Networking, Cybersecurity, and Emerging Technologies will give you the edge you need to harness AI for your benefit. Learn how AI can efficiently identify shadow data, fortify security measures, generate predictive analytics in real time, and so much more. In this comprehensive guide, Cisco professionals Omar Santos, Samer Salam, and Hazim Dahir engage you in both AI application and theory through practical case studies and predictions of future trends, which makes this book not just a valuable guide for today, but an indispensable resource for tomorrow. You'll discover how AI is building robust bridges in collaboration tools and turning IoT into a super-intelligent network of devices so you can quickly identify and resolve network security threats while enhancing network performance.

Название: CompTIA Security+ SY0-701 Practice Tests & PBQs: Exam SY0-701
Автор: Nikolaos Gorgotsias
Издательство: ExamsDigest LLC. and LabsDigest LLC
Год: December 10, 2023
Страниц: 1620
Язык: английский
Формат: pdf
Размер: 12.2 MB

Are you preparing for the CompTIA Security+ SY0-701 exam? Assess your exam readiness with these Practice Tests to maximize your chance of passing your CompTIA Security+ SY0-701 first time. The ebook is fully updated to reflect the latest CompTIA Security+ SY0-701 exam. These 1200+ practice exam questions will prepare you thoroughly for the real exam so that you get to ace your exam with confidence. Presented with and without answers so you can study or simulate an exam. There are 1200+ practice exam questions, covering all domains of the latest CompTIA Security+ SY0-701 exam blueprint. Each question reflects the difficulty of the real CompTIA Security+ SY0-701 exam. With these Practice Tests, you'll know when you are ready to ace your CompTIA Security+ SY0-701 exam! We recommend reviewing these practice questions until you’re confident in all areas and ready to achieve a great score! Also, claim your free access to examsdigest.com in order to get all the benefits.

Название: Federated Learning for Future Intelligent Wireless Networks
Автор: Yao Sun, Chaoqun You, Gang Feng
Издательство: Wiley-IEEE Press
Год: 2024
Страниц: 306
Язык: английский
Формат: pdf (true)
Размер: 10.1 MB

Explore the concepts, algorithms, and applications underlying Federated Learning. In Federated Learning for Future Intelligent Wireless Networks, a team of distinguished researchers deliver a robust and insightful collection of resources covering the foundational concepts and algorithms powering Federated Learning, as well as explanations of how they can be used in wireless communication systems. The editors have included works that examine how communication resource provision affects Federated Learning performance, accuracy, convergence, scalability, and security and privacy. Federated Learning (FL) has been widely acknowledged as one of the most essential enablers to bring network edge intelligence into reality, as it can enable collaborative training of ML models while enhancing individual user privacy and data security. Empowered by the growing computing capabilities of UEs, FL trains ML models locally on each device where the raw data never leaves the device. Specifically, FL uses an iterative approach that requires a number of global iterations to achieve a global model accuracy. In each global iteration, UEs take a number of local iterations up to a local model accuracy. This book would explore recent advances in the theory and practice of FL, especially when it is applied to wireless communication systems.

Название: Communication Efficient Federated Learning for Wireless Networks
Автор: Mingzhe Chen, Shuguang Cui
Издательство: Springer
Серия: Wireless Networks
Год: 2024
Страниц: 189
Язык: английский
Формат: pdf (true), epub
Размер: 24.2 MB

This book provides a comprehensive study of Federated Learning (FL) over wireless networks. It consists of three main parts: (a) Fundamentals and preliminaries of FL, (b) analysis and optimization of FL over wireless networks, and © applications of wireless FL for Internet-of-Things systems. In particular, in the first part, the authors provide a detailed overview on widely-studied FL framework. In the second part of this book, the authors comprehensively discuss three key wireless techniques including wireless resource management, quantization, and over-the-air computation to support the deployment of FL over realistic wireless networks. It also presents several solutions based on optimization theory, graph theory and machine learning to optimize the performance of FL over wireless networks. In the third part of this book, the authors introduce the use of wireless FL algorithms for autonomous vehicle control and mobile edge computing optimization. Machine Learning and data-driven approaches have recently received considerable attention as key enablers for next-generation intelligent networks. Currently, most existing learning solutions for wireless networks rely on centralizing the training and inference processes by uploading data generated at edge devices to data centers.

Название: Learning Techniques for the Internet of Things
Автор: Praveen Kumar Donta, Abhishek Hazra, Lauri Loven
Издательство: Springer
Год: 2024
Страниц: 334
Язык: английский
Формат: pdf (true), epub
Размер: 31.7 MB

Learning for the Internet of Things is a combination of advanced learning techniques for the Internet of Things (IoT) encompassing a range of cutting-edge approaches, including Deep Learning with CNNs, RNNs, and transformers, Federated Learning, edge AI for local data processing, reinforcement learning for autonomous decision-making, and their applications in real time. The book is structured into thirteen chapters; each comes with its own dedicated contributions and future research directions. Chapter 1 introduces IoT and the use of Edge computing, particularly cloud computing, and mobile edge computing. This chapter also mentions the use of edge computing in various real-time applications such as healthcare, manufacturing, agriculture, and transportation. Chapter 2 motivates mathematical modeling for Federated Learning systems with respect to IoT and its applications. Further Chapter 3 extends the discussion of Federated Learning for IoT, which has emerged as a privacy-preserving distributed Machine Learning approach.