Machine Learning For Embedded System Security
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Machine Learning For Embedded System Security
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Author : Basel Halak
language : en
Publisher: Springer Nature
Release Date : 2022-04-22
Machine Learning For Embedded System Security written by Basel Halak and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-04-22 with Technology & Engineering categories.
This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities.
The Intersection Of 6g Ai Machine Learning And Embedded Systems
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Author : Shruti Sharma
language : en
Publisher: CRC Press
Release Date : 2025-03-24
The Intersection Of 6g Ai Machine Learning And Embedded Systems written by Shruti Sharma and has been published by CRC Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2025-03-24 with Technology & Engineering categories.
This comprehensive guide to the emerging areas and synergistic relationships among the domains of 6G, machine learning, and embedded systems offers readers a detailed analysis of their converging paths and contributions to the development of intelligent wireless systems. Readers will gain a solid understanding of the principles and technologies behind 6G, machine learning, and embedded systems. They will learn how these three areas intertwine and why this intersection is pivotal for the next generation of wireless technologies. The contributors to this volume present a thorough and detailed analysis of this technology, highlighting its promising features, underlying technologies, and potential applications. The book first explores various applications of machine learning algorithms in areas such as network optimization, resource allocation, interference management, and intelligent data processing and analysis. Design considerations and challenges are presented, and case studies of innovative applications, such as smart cities, autonomous vehicles, healthcare, and industrial automation, are examined. The book concludes with a discussion of future trends and opportunities in this rapidly evolving field. Readers will benefit from the theoretical foundations and practical insights presented within and will be prepared to address future challenges and opportunities in these three fields. This book is a valuable resource for academic researchers and industry professionals working in the fields of wireless communication, machine learning, embedded systems, and artificial intelligence.
Machine Learning For Embedded System Security
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Author : Basel Halak
language : en
Publisher:
Release Date : 2022
Machine Learning For Embedded System Security written by Basel Halak and has been published by this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022 with categories.
This book comprehensively covers the state-of-the-art security applications of machine learning techniques. The first part explains the emerging solutions for anti-tamper design, IC Counterfeits detection and hardware Trojan identification. It also explains the latest development of deep-learning-based modeling attacks on physically unclonable functions and outlines the design principles of more resilient PUF architectures. The second discusses the use of machine learning to mitigate the risks of security attacks on cyber-physical systems, with a particular focus on power plants. The third part provides an in-depth insight into the principles of malware analysis in embedded systems and describes how the usage of supervised learning techniques provides an effective approach to tackle software vulnerabilities. Discusses emerging technologies used to develop intelligent tamper detection techniques, using machine learning; Includes a comprehensive summary of how machine learning is used to combat IC counterfeit and to detect Trojans; Describes how machine learning algorithms are used to enhance the security of physically unclonable functions (PUFs); It describes, in detail, the principles of the state-of-the-art countermeasures for hardware, software, and cyber-physical attacks on embedded systems. .
Machine Learning For Cyber Security
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Author : Preeti Malik
language : en
Publisher: Walter de Gruyter GmbH & Co KG
Release Date : 2022-12-05
Machine Learning For Cyber Security written by Preeti Malik and has been published by Walter de Gruyter GmbH & Co KG this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-12-05 with Business & Economics categories.
This book shows how machine learning (ML) methods can be used to enhance cyber security operations, including detection, modeling, monitoring as well as defense against threats to sensitive data and security systems. Filling an important gap between ML and cyber security communities, it discusses topics covering a wide range of modern and practical ML techniques, frameworks and tools.
Hardware Accelerator Systems For Artificial Intelligence And Machine Learning
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Author :
language : en
Publisher: Academic Press
Release Date : 2021-03-28
Hardware Accelerator Systems For Artificial Intelligence And Machine Learning written by and has been published by Academic Press this book supported file pdf, txt, epub, kindle and other format this book has been release on 2021-03-28 with Mathematics categories.
Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into artificial Intelligence and the growth it has seen with the advent of Deep Neural Networks (DNNs) and Machine Learning. Updates in this release include chapters on Hardware accelerator systems for artificial intelligence and machine learning, Introduction to Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Deep Learning with GPUs, Edge Computing Optimization of Deep Learning Models for Specialized Tensor Processing Architectures, Architecture of NPU for DNN, Hardware Architecture for Convolutional Neural Network for Image Processing, FPGA based Neural Network Accelerators, and much more. - Updates on new information on the architecture of GPU, NPU and DNN - Discusses In-memory computing, Machine intelligence and Quantum computing - Includes sections on Hardware Accelerator Systems to improve processing efficiency and performance
Beginning Artificial Intelligence With The Raspberry Pi
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Author : Donald J. Norris
language : en
Publisher: Apress
Release Date : 2017-06-05
Beginning Artificial Intelligence With The Raspberry Pi written by Donald J. Norris and has been published by Apress this book supported file pdf, txt, epub, kindle and other format this book has been release on 2017-06-05 with Computers categories.
Gain a gentle introduction to the world of Artificial Intelligence (AI) using the Raspberry Pi as the computing platform. Most of the major AI topics will be explored, including expert systems, machine learning both shallow and deep, fuzzy logic control, and more! AI in action will be demonstrated using the Python language on the Raspberry Pi. The Prolog language will also be introduced and used to demonstrate fundamental AI concepts. In addition, the Wolfram language will be used as part of the deep machine learning demonstrations. A series of projects will walk you through how to implement AI concepts with the Raspberry Pi. Minimal expense is needed for the projects as only a few sensors and actuators will be required. Beginners and hobbyists can jump right in to creating AI projects with the Raspberry PI using this book. What You'll Learn What AI is and—as importantly—what it is not Inference and expert systems Machine learning both shallow and deep Fuzzy logic and how to apply to an actual control system When AI might be appropriate to include in a system Constraints and limitations of the Raspberry Pi AI implementation Who This Book Is For Hobbyists, makers, engineers involved in designing autonomous systems and wanting to gain an education in fundamental AI concepts, and non-technical readers who want to understand what AI is and how it might affect their lives.
Cryptology And Network Security With Machine Learning
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Author : Atul Chaturvedi
language : en
Publisher: Springer Nature
Release Date : 2024-04-22
Cryptology And Network Security With Machine Learning written by Atul Chaturvedi and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-22 with Technology & Engineering categories.
The book features original papers from International Conference on Cryptology & Network Security with Machine Learning (ICCNSML 2023), organized by PSIT, Kanpur, India during 27–29 October 2023. This conference proceeding provides the understanding of core concepts of Cryptology and Network Security with ML in data communication. The book covers research papers in public key cryptography, elliptic curve cryptography, post-quantum cryptography, lattice based cryptography, non-commutative ring-based cryptography, cryptocurrency, authentication, key agreement, Hash functions, block/stream ciphers, polynomial-based cryptography, code-based cryptography, NTRU cryptosystems, security and privacy in machine learning, blockchain, IoT security, wireless security protocols, cryptanalysis, number theory, quantum computing, cryptographic aspects of network security, complexity theory, and cryptography with machine learning.
Deep Learning For Computational Problems In Hardware Security
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Author : Pranesh Santikellur
language : en
Publisher: Springer Nature
Release Date : 2022-09-15
Deep Learning For Computational Problems In Hardware Security written by Pranesh Santikellur and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-09-15 with Technology & Engineering categories.
The book discusses a broad overview of traditional machine learning methods and state-of-the-art deep learning practices for hardware security applications, in particular the techniques of launching potent "modeling attacks" on Physically Unclonable Function (PUF) circuits, which are promising hardware security primitives. The volume is self-contained and includes a comprehensive background on PUF circuits, and the necessary mathematical foundation of traditional and advanced machine learning techniques such as support vector machines, logistic regression, neural networks, and deep learning. This book can be used as a self-learning resource for researchers and practitioners of hardware security, and will also be suitable for graduate-level courses on hardware security and application of machine learning in hardware security. A stand-out feature of the book is the availability of reference software code and datasets to replicate the experiments described in the book.
Machine Learning For Cyber Physical System Advances And Challenges
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Author : Janmenjoy Nayak
language : en
Publisher: Springer Nature
Release Date : 2024-04-11
Machine Learning For Cyber Physical System Advances And Challenges written by Janmenjoy Nayak and has been published by Springer Nature this book supported file pdf, txt, epub, kindle and other format this book has been release on 2024-04-11 with Computers categories.
This book provides a comprehensive platform for learning the state-of-the-art machine learning algorithms for solving several cybersecurity issues. It is helpful in guiding for the implementation of smart machine learning solutions to detect various cybersecurity problems and make the users to understand in combating malware, detect spam, and fight financial fraud to mitigate cybercrimes. With an effective analysis of cyber-physical data, it consists of the solution for many real-life problems such as anomaly detection, IoT-based framework for security and control, manufacturing control system, fault detection, smart cities, risk assessment of cyber-physical systems, medical diagnosis, smart grid systems, biometric-based physical and cybersecurity systems using advance machine learning approach. Filling an important gap between machine learning and cybersecurity communities, it discusses topics covering a wide range of modern and practical advance machine learning techniques, frameworks, and development tools to enable readers to engage with the cutting-edge research across various aspects of cybersecurity.
Research Anthology On Machine Learning Techniques Methods And Applications
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Author : Management Association, Information Resources
language : en
Publisher: IGI Global
Release Date : 2022-05-13
Research Anthology On Machine Learning Techniques Methods And Applications written by Management Association, Information Resources and has been published by IGI Global this book supported file pdf, txt, epub, kindle and other format this book has been release on 2022-05-13 with Computers categories.
Machine learning continues to have myriad applications across industries and fields. To ensure this technology is utilized appropriately and to its full potential, organizations must better understand exactly how and where it can be adapted. Further study on the applications of machine learning is required to discover its best practices, challenges, and strategies. The Research Anthology on Machine Learning Techniques, Methods, and Applications provides a thorough consideration of the innovative and emerging research within the area of machine learning. The book discusses how the technology has been used in the past as well as potential ways it can be used in the future to ensure industries continue to develop and grow. Covering a range of topics such as artificial intelligence, deep learning, cybersecurity, and robotics, this major reference work is ideal for computer scientists, managers, researchers, scholars, practitioners, academicians, instructors, and students.