Machine Learning For Embedded System Security

Download Machine Learning For Embedded System Security full books in PDF, epub, and Kindle. Read online Machine Learning For Embedded System Security ebook anywhere anytime directly on your device. Fast Download speed and no annoying ads. We cannot guarantee that every ebooks is available!

Machine Learning for Embedded System Security

Author : Basel Halak
Publisher : Springer Nature
ISBN 13 : 3030941787
Total Pages : 166 pages
Book Rating : 4.0/5 (39 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning for Embedded System Security by : Basel Halak

Download or read book Machine Learning for Embedded System Security written by Basel Halak and published by Springer Nature. This book was released on 2022-04-22 with total page 166 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Author : Sudeep Pasricha
Publisher : Springer Nature
ISBN 13 : 3031399323
Total Pages : 481 pages
Book Rating : 4.0/5 (313 download)

DOWNLOAD NOW!

Book Synopsis Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing by : Sudeep Pasricha

Download or read book Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing written by Sudeep Pasricha and published by Springer Nature. This book was released on 2023-10-09 with total page 481 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

AI-Enabled Threat Detection and Security Analysis for Industrial IoT

Author : Hadis Karimipour
Publisher : Springer Nature
ISBN 13 : 3030766136
Total Pages : 250 pages
Book Rating : 4.0/5 (37 download)

DOWNLOAD NOW!

Book Synopsis AI-Enabled Threat Detection and Security Analysis for Industrial IoT by : Hadis Karimipour

Download or read book AI-Enabled Threat Detection and Security Analysis for Industrial IoT written by Hadis Karimipour and published by Springer Nature. This book was released on 2021-08-03 with total page 250 pages. Available in PDF, EPUB and Kindle. Book excerpt: This contributed volume provides the state-of-the-art development on security and privacy for cyber-physical systems (CPS) and industrial Internet of Things (IIoT). More specifically, this book discusses the security challenges in CPS and IIoT systems as well as how Artificial Intelligence (AI) and Machine Learning (ML) can be used to address these challenges. Furthermore, this book proposes various defence strategies, including intelligent cyber-attack and anomaly detection algorithms for different IIoT applications. Each chapter corresponds to an important snapshot including an overview of the opportunities and challenges of realizing the AI in IIoT environments, issues related to data security, privacy and application of blockchain technology in the IIoT environment. This book also examines more advanced and specific topics in AI-based solutions developed for efficient anomaly detection in IIoT environments. Different AI/ML techniques including deep representation learning, Snapshot Ensemble Deep Neural Network (SEDNN), federated learning and multi-stage learning are discussed and analysed as well. Researchers and professionals working in computer security with an emphasis on the scientific foundations and engineering techniques for securing IIoT systems and their underlying computing and communicating systems will find this book useful as a reference. The content of this book will be particularly useful for advanced-level students studying computer science, computer technology, cyber security, and information systems. It also applies to advanced-level students studying electrical engineering and system engineering, who would benefit from the case studies.

Embedded Systems Security

Author : David Kleidermacher
Publisher : Elsevier
ISBN 13 : 0123868866
Total Pages : 417 pages
Book Rating : 4.1/5 (238 download)

DOWNLOAD NOW!

Book Synopsis Embedded Systems Security by : David Kleidermacher

Download or read book Embedded Systems Security written by David Kleidermacher and published by Elsevier. This book was released on 2012-03-16 with total page 417 pages. Available in PDF, EPUB and Kindle. Book excerpt: Front Cover; Dedication; Embedded Systems Security: Practical Methods for Safe and Secure Softwareand Systems Development; Copyright; Contents; Foreword; Preface; About this Book; Audience; Organization; Approach; Acknowledgements; Chapter 1 -- Introduction to Embedded Systems Security; 1.1What is Security?; 1.2What is an Embedded System?; 1.3Embedded Security Trends; 1.4Security Policies; 1.5Security Threats; 1.6Wrap-up; 1.7Key Points; 1.8 Bibliography and Notes; Chapter 2 -- Systems Software Considerations; 2.1The Role of the Operating System; 2.2Multiple Independent Levels of Security.

Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing

Author : Sudeep Pasricha
Publisher : Springer Nature
ISBN 13 : 303140677X
Total Pages : 571 pages
Book Rating : 4.0/5 (314 download)

DOWNLOAD NOW!

Book Synopsis Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing by : Sudeep Pasricha

Download or read book Embedded Machine Learning for Cyber-Physical, IoT, and Edge Computing written by Sudeep Pasricha and published by Springer Nature. This book was released on 2023-11-07 with total page 571 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents recent advances towards the goal of enabling efficient implementation of machine learning models on resource-constrained systems, covering different application domains. The focus is on presenting interesting and new use cases of applying machine learning to innovative application domains, exploring the efficient hardware design of efficient machine learning accelerators, memory optimization techniques, illustrating model compression and neural architecture search techniques for energy-efficient and fast execution on resource-constrained hardware platforms, and understanding hardware-software codesign techniques for achieving even greater energy, reliability, and performance benefits. Discusses efficient implementation of machine learning in embedded, CPS, IoT, and edge computing; Offers comprehensive coverage of hardware design, software design, and hardware/software co-design and co-optimization; Describes real applications to demonstrate how embedded, CPS, IoT, and edge applications benefit from machine learning.

Cyber Security Meets Machine Learning

Author : Xiaofeng Chen
Publisher : Springer Nature
ISBN 13 : 9813367261
Total Pages : 168 pages
Book Rating : 4.8/5 (133 download)

DOWNLOAD NOW!

Book Synopsis Cyber Security Meets Machine Learning by : Xiaofeng Chen

Download or read book Cyber Security Meets Machine Learning written by Xiaofeng Chen and published by Springer Nature. This book was released on 2021-07-02 with total page 168 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine learning boosts the capabilities of security solutions in the modern cyber environment. However, there are also security concerns associated with machine learning models and approaches: the vulnerability of machine learning models to adversarial attacks is a fatal flaw in the artificial intelligence technologies, and the privacy of the data used in the training and testing periods is also causing increasing concern among users. This book reviews the latest research in the area, including effective applications of machine learning methods in cybersecurity solutions and the urgent security risks related to the machine learning models. The book is divided into three parts: Cyber Security Based on Machine Learning; Security in Machine Learning Methods and Systems; and Security and Privacy in Outsourced Machine Learning. Addressing hot topics in cybersecurity and written by leading researchers in the field, the book features self-contained chapters to allow readers to select topics that are relevant to their needs. It is a valuable resource for all those interested in cybersecurity and robust machine learning, including graduate students and academic and industrial researchers, wanting to gain insights into cutting-edge research topics, as well as related tools and inspiring innovations.

Learning in Embedded Systems

Author : Leslie Pack Kaelbling
Publisher : MIT Press
ISBN 13 : 9780262111744
Total Pages : 206 pages
Book Rating : 4.1/5 (117 download)

DOWNLOAD NOW!

Book Synopsis Learning in Embedded Systems by : Leslie Pack Kaelbling

Download or read book Learning in Embedded Systems written by Leslie Pack Kaelbling and published by MIT Press. This book was released on 1993 with total page 206 pages. Available in PDF, EPUB and Kindle. Book excerpt: Learning to perform complex action strategies is an important problem in the fields of artificial intelligence, robotics and machine learning. Presenting interesting, new experimental results, Learning in Embedded Systems explores algorithms that learn efficiently from trial and error experience with an external world. The text is a detailed exploration of the problem of learning action strategies in the context of designing embedded systems that adapt their behaviour to a complex, changing environment. Such systems include mobile robots, factory process controllers and long-term software databases.

Machine Learning and Security

Author : Clarence Chio
Publisher : "O'Reilly Media, Inc."
ISBN 13 : 1491979879
Total Pages : 385 pages
Book Rating : 4.4/5 (919 download)

DOWNLOAD NOW!

Book Synopsis Machine Learning and Security by : Clarence Chio

Download or read book Machine Learning and Security written by Clarence Chio and published by "O'Reilly Media, Inc.". This book was released on 2018-01-26 with total page 385 pages. Available in PDF, EPUB and Kindle. Book excerpt: Can machine learning techniques solve our computer security problems and finally put an end to the cat-and-mouse game between attackers and defenders? Or is this hope merely hype? Now you can dive into the science and answer this question for yourself. With this practical guide, you’ll explore ways to apply machine learning to security issues such as intrusion detection, malware classification, and network analysis. Machine learning and security specialists Clarence Chio and David Freeman provide a framework for discussing the marriage of these two fields, as well as a toolkit of machine-learning algorithms that you can apply to an array of security problems. This book is ideal for security engineers and data scientists alike. Learn how machine learning has contributed to the success of modern spam filters Quickly detect anomalies, including breaches, fraud, and impending system failure Conduct malware analysis by extracting useful information from computer binaries Uncover attackers within the network by finding patterns inside datasets Examine how attackers exploit consumer-facing websites and app functionality Translate your machine learning algorithms from the lab to production Understand the threat attackers pose to machine learning solutions

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John MacIntyre
Publisher : Springer Nature
ISBN 13 : 3030627462
Total Pages : 887 pages
Book Rating : 4.0/5 (36 download)

DOWNLOAD NOW!

Book Synopsis The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by : John MacIntyre

Download or read book The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John MacIntyre and published by Springer Nature. This book was released on 2020-11-04 with total page 887 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John Macintyre
Publisher : Springer Nature
ISBN 13 : 3030895114
Total Pages : 999 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by : John Macintyre

Download or read book The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John Macintyre and published by Springer Nature. This book was released on 2021-11-02 with total page 999 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

Embedded Devices and Internet of Things

Author : Adesh Kumar
Publisher : CRC Press
ISBN 13 : 1040113893
Total Pages : 361 pages
Book Rating : 4.0/5 (41 download)

DOWNLOAD NOW!

Book Synopsis Embedded Devices and Internet of Things by : Adesh Kumar

Download or read book Embedded Devices and Internet of Things written by Adesh Kumar and published by CRC Press. This book was released on 2024-09-11 with total page 361 pages. Available in PDF, EPUB and Kindle. Book excerpt: The text comprehensively discusses machine-to-machine communication in real-time, low-power system design and estimation using field programmable gate arrays, PID, hardware, accelerators, and software integration for service applications. It further covers the recent advances in embedded computing and IoT for healthcare systems. The text explains the use of low-power devices such as microcontrollers in executing deep neural networks, and other machine learning techniques. This book: Discusses the embedded system software and hardware methodologies for system-on-chip and FPGA Illustrates low-power embedded applications, AI-based system design, PID control design, and CNN hardware design Highlights the integration of advanced 5G communication technologies with embedded systems Explains weather prediction modeling, embedded machine learning, and RTOS Highlights the significance of machine-learning techniques on the Internet of Things (IoT), real-time embedded system design, communication, and healthcare applications, and provides insights on IoT applications in education, fault attacks, security concerns, AI integration, banking, blockchain, intelligent tutoring systems, and smart technologies It is primarily written for senior undergraduates, graduate students, and academic researchers in the fields of electrical engineering, electronics and communications engineering, and computer engineering.

Beginning Artificial Intelligence with the Raspberry Pi

Author : Donald J. Norris
Publisher : Apress
ISBN 13 : 1484227433
Total Pages : 379 pages
Book Rating : 4.4/5 (842 download)

DOWNLOAD NOW!

Book Synopsis Beginning Artificial Intelligence with the Raspberry Pi by : Donald J. Norris

Download or read book Beginning Artificial Intelligence with the Raspberry Pi written by Donald J. Norris and published by Apress. This book was released on 2017-06-05 with total page 379 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John Macintyre
Publisher : Springer Nature
ISBN 13 : 3030895084
Total Pages : 1169 pages
Book Rating : 4.0/5 (38 download)

DOWNLOAD NOW!

Book Synopsis The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by : John Macintyre

Download or read book The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John Macintyre and published by Springer Nature. This book was released on 2021-10-27 with total page 1169 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of the 2020 2nd International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2021), online conference, on 30 October 2021. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

Author : John MacIntyre
Publisher : Springer Nature
ISBN 13 : 3030627438
Total Pages : 907 pages
Book Rating : 4.0/5 (36 download)

DOWNLOAD NOW!

Book Synopsis The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy by : John MacIntyre

Download or read book The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy written by John MacIntyre and published by Springer Nature. This book was released on 2020-11-03 with total page 907 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book presents the proceedings of The 2020 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy (SPIoT-2020), held in Shanghai, China, on November 6, 2020. Due to the COVID-19 outbreak problem, SPIoT-2020 conference was held online by Tencent Meeting. It provides comprehensive coverage of the latest advances and trends in information technology, science and engineering, addressing a number of broad themes, including novel machine learning and big data analytics methods for IoT security, data mining and statistical modelling for the secure IoT and machine learning-based security detecting protocols, which inspire the development of IoT security and privacy technologies. The contributions cover a wide range of topics: analytics and machine learning applications to IoT security; data-based metrics and risk assessment approaches for IoT; data confidentiality and privacy in IoT; and authentication and access control for data usage in IoT. Outlining promising future research directions, the book is a valuable resource for students, researchers and professionals and provides a useful reference guide for newcomers to the IoT security and privacy field.

AI Embedded Assurance for Cyber Systems

Author : Cliff Wang
Publisher : Springer Nature
ISBN 13 : 3031426371
Total Pages : 252 pages
Book Rating : 4.0/5 (314 download)

DOWNLOAD NOW!

Book Synopsis AI Embedded Assurance for Cyber Systems by : Cliff Wang

Download or read book AI Embedded Assurance for Cyber Systems written by Cliff Wang and published by Springer Nature. This book was released on 2024-01-13 with total page 252 pages. Available in PDF, EPUB and Kindle. Book excerpt: The rapid growth and reliance on cyber systems have permeated our society, government, and military which is demonstrated in this book. The authors discuss how AI-powered cyber systems are designed to protect against cyber threats and ensure the security and reliability of digital systems using artificial intelligence (AI) technologies. As AI becomes more integrated into various aspects of our lives, the need for reliable and trustworthy AI systems becomes increasingly important. This book is an introduction to all of the above-mentioned areas in the context of AI Embedded Assurance for Cyber Systems. This book has three themes. First, the AI/ML for digital forensics theme focuses on developing AI and ML powered forensic tools, techniques, software, and hardware. Second, the AI/ML for cyber physical system theme describes that AI/ML plays an enabling role to boost the development of cyber physical systems (CPS), especially in strengthening the security and privacy of CPS. Third, the AI/ML for cyber analysis theme focuses on using AI/ML to analyze tons of data in a timely manner and identify many complex threat patterns. This book is designed for undergraduates, graduate students in computer science and researchers in an interdisciplinary area of cyber forensics and AI embedded security applications. It is also useful for practitioners who would like to adopt AIs to solve cyber security problems.

Introduction to Machine Learning with Security

Author : Pramod Gupta
Publisher : Springer Nature
ISBN 13 : 3031591704
Total Pages : 509 pages
Book Rating : 4.0/5 (315 download)

DOWNLOAD NOW!

Book Synopsis Introduction to Machine Learning with Security by : Pramod Gupta

Download or read book Introduction to Machine Learning with Security written by Pramod Gupta and published by Springer Nature. This book was released on with total page 509 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Hardware Accelerator Systems for Artificial Intelligence and Machine Learning

Author :
Publisher : Academic Press
ISBN 13 : 0128231246
Total Pages : 416 pages
Book Rating : 4.1/5 (282 download)

DOWNLOAD NOW!

Book Synopsis Hardware Accelerator Systems for Artificial Intelligence and Machine Learning by :

Download or read book Hardware Accelerator Systems for Artificial Intelligence and Machine Learning written by and published by Academic Press. This book was released on 2021-03-28 with total page 416 pages. Available in PDF, EPUB and Kindle. Book excerpt: Hardware Accelerator Systems for Artificial Intelligence and Machine Learning, Volume 122 delves into arti?cial 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