Modern Approaches In Iot And Machine Learning For Cyber Security

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Modern Approaches in IoT and Machine Learning for Cyber Security

Author : Vinit Kumar Gunjan
Publisher : Springer Nature
ISBN 13 : 3031099559
Total Pages : 415 pages
Book Rating : 4.0/5 (31 download)

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Book Synopsis Modern Approaches in IoT and Machine Learning for Cyber Security by : Vinit Kumar Gunjan

Download or read book Modern Approaches in IoT and Machine Learning for Cyber Security written by Vinit Kumar Gunjan and published by Springer Nature. This book was released on 2024-01-08 with total page 415 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book examines the cyber risks associated with Internet of Things (IoT) and highlights the cyber security capabilities that IoT platforms must have in order to address those cyber risks effectively. The chapters fuse together deep cyber security expertise with artificial intelligence (AI), machine learning, and advanced analytics tools, which allows readers to evaluate, emulate, outpace, and eliminate threats in real time. The book’s chapters are written by experts of IoT and machine learning to help examine the computer-based crimes of the next decade. They highlight on automated processes for analyzing cyber frauds in the current systems and predict what is on the horizon. This book is applicable for researchers and professionals in cyber security, AI, and IoT.

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)

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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.

Deep Learning Approaches for Security Threats in IoT Environments

Author : Mohamed Abdel-Basset
Publisher : John Wiley & Sons
ISBN 13 : 1119884160
Total Pages : 388 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Deep Learning Approaches for Security Threats in IoT Environments by : Mohamed Abdel-Basset

Download or read book Deep Learning Approaches for Security Threats in IoT Environments written by Mohamed Abdel-Basset and published by John Wiley & Sons. This book was released on 2022-11-22 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: Deep Learning Approaches for Security Threats in IoT Environments An expert discussion of the application of deep learning methods in the IoT security environment In Deep Learning Approaches for Security Threats in IoT Environments, a team of distinguished cybersecurity educators deliver an insightful and robust exploration of how to approach and measure the security of Internet-of-Things (IoT) systems and networks. In this book, readers will examine critical concepts in artificial intelligence (AI) and IoT, and apply effective strategies to help secure and protect IoT networks. The authors discuss supervised, semi-supervised, and unsupervised deep learning techniques, as well as reinforcement and federated learning methods for privacy preservation. This book applies deep learning approaches to IoT networks and solves the security problems that professionals frequently encounter when working in the field of IoT, as well as providing ways in which smart devices can solve cybersecurity issues. Readers will also get access to a companion website with PowerPoint presentations, links to supporting videos, and additional resources. They’ll also find: A thorough introduction to artificial intelligence and the Internet of Things, including key concepts like deep learning, security, and privacy Comprehensive discussions of the architectures, protocols, and standards that form the foundation of deep learning for securing modern IoT systems and networks In-depth examinations of the architectural design of cloud, fog, and edge computing networks Fulsome presentations of the security requirements, threats, and countermeasures relevant to IoT networks Perfect for professionals working in the AI, cybersecurity, and IoT industries, Deep Learning Approaches for Security Threats in IoT Environments will also earn a place in the libraries of undergraduate and graduate students studying deep learning, cybersecurity, privacy preservation, and the security of IoT networks.

Convergence of Deep Learning in Cyber-IoT Systems and Security

Author : Rajdeep Chakraborty
Publisher : John Wiley & Sons
ISBN 13 : 111985766X
Total Pages : 485 pages
Book Rating : 4.1/5 (198 download)

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Book Synopsis Convergence of Deep Learning in Cyber-IoT Systems and Security by : Rajdeep Chakraborty

Download or read book Convergence of Deep Learning in Cyber-IoT Systems and Security written by Rajdeep Chakraborty and published by John Wiley & Sons. This book was released on 2022-11-08 with total page 485 pages. Available in PDF, EPUB and Kindle. Book excerpt: CONVERGENCE OF DEEP LEARNING IN CYBER-IOT SYSTEMS AND SECURITY In-depth analysis of Deep Learning-based cyber-IoT systems and security which will be the industry leader for the next ten years. The main goal of this book is to bring to the fore unconventional cryptographic methods to provide cyber security, including cyber-physical system security and IoT security through deep learning techniques and analytics with the study of all these systems. This book provides innovative solutions and implementation of deep learning-based models in cyber-IoT systems, as well as the exposed security issues in these systems. The 20 chapters are organized into four parts. Part I gives the various approaches that have evolved from machine learning to deep learning. Part II presents many innovative solutions, algorithms, models, and implementations based on deep learning. Part III covers security and safety aspects with deep learning. Part IV details cyber-physical systems as well as a discussion on the security and threats in cyber-physical systems with probable solutions. Audience Researchers and industry engineers in computer science, information technology, electronics and communication, cybersecurity and cryptography.

Artificial Intelligence and Cyber Security in Industry 4.0

Author : Velliangiri Sarveshwaran
Publisher : Springer Nature
ISBN 13 : 9819921155
Total Pages : 374 pages
Book Rating : 4.8/5 (199 download)

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Book Synopsis Artificial Intelligence and Cyber Security in Industry 4.0 by : Velliangiri Sarveshwaran

Download or read book Artificial Intelligence and Cyber Security in Industry 4.0 written by Velliangiri Sarveshwaran and published by Springer Nature. This book was released on 2023-07-15 with total page 374 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides theoretical background and state-of-the-art findings in artificial intelligence and cybersecurity for industry 4.0 and helps in implementing AI-based cybersecurity applications. Machine learning-based security approaches are vulnerable to poison datasets which can be caused by a legitimate defender's misclassification or attackers aiming to evade detection by contaminating the training data set. There also exist gaps between the test environment and the real world. Therefore, it is critical to check the potentials and limitations of AI-based security technologies in terms of metrics such as security, performance, cost, time, and consider how to incorporate them into the real world by addressing the gaps appropriately. This book focuses on state-of-the-art findings from both academia and industry in big data security relevant sciences, technologies, and applications.

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)

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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.

Machine Learning Approach for Cloud Data Analytics in IoT

Author : Sachi Nandan Mohanty
Publisher : John Wiley & Sons
ISBN 13 : 1119785855
Total Pages : 528 pages
Book Rating : 4.1/5 (197 download)

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Book Synopsis Machine Learning Approach for Cloud Data Analytics in IoT by : Sachi Nandan Mohanty

Download or read book Machine Learning Approach for Cloud Data Analytics in IoT written by Sachi Nandan Mohanty and published by John Wiley & Sons. This book was released on 2021-07-14 with total page 528 pages. Available in PDF, EPUB and Kindle. Book excerpt: Machine Learning Approach for Cloud Data Analytics in IoT The book covers the multidimensional perspective of machine learning through the perspective of cloud computing and Internet of Things ranging from fundamentals to advanced applications Sustainable computing paradigms like cloud and fog are capable of handling issues related to performance, storage and processing, maintenance, security, efficiency, integration, cost, energy and latency in an expeditious manner. In order to expedite decision-making involved in the complex computation and processing of collected data, IoT devices are connected to the cloud or fog environment. Since machine learning as a service provides the best support in business intelligence, organizations have been making significant investments in this technology. Machine Learning Approach for Cloud Data Analytics in IoT elucidates some of the best practices and their respective outcomes in cloud and fog computing environments. It focuses on all the various research issues related to big data storage and analysis, large-scale data processing, knowledge discovery and knowledge management, computational intelligence, data security and privacy, data representation and visualization, and data analytics. The featured technologies presented in the book optimizes various industry processes using business intelligence in engineering and technology. Light is also shed on cloud-based embedded software development practices to integrate complex machines so as to increase productivity and reduce operational costs. The various practices of data science and analytics which are used in all sectors to understand big data and analyze massive data patterns are also detailed in the book.

Utilizing Generative AI for Cyber Defense Strategies

Author : Jhanjhi, Noor Zaman
Publisher : IGI Global
ISBN 13 :
Total Pages : 546 pages
Book Rating : 4.3/5 (693 download)

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Book Synopsis Utilizing Generative AI for Cyber Defense Strategies by : Jhanjhi, Noor Zaman

Download or read book Utilizing Generative AI for Cyber Defense Strategies written by Jhanjhi, Noor Zaman and published by IGI Global. This book was released on 2024-09-12 with total page 546 pages. Available in PDF, EPUB and Kindle. Book excerpt: As cyber threats become increasingly sophisticated, the need for innovative defense strategies becomes urgent. Generative artificial intelligence (AI) offers a revolutionary approach to enhance cybersecurity. By utilizing advanced algorithms, data analysis, and machine learning, generative AI can simulate complex attack scenarios, identify vulnerabilities, and develop proactive defense mechanisms while adapting to modern-day cyber-attacks. AI strengthens current organizational security while offering quick, effective responses to emerging threats. Decisive strategies are needed to integrate generative AI into businesses defense strategies and protect organizations from attacks, secure digital data, and ensure safe business processes. Utilizing Generative AI for Cyber Defense Strategies explores the utilization of generative AI tools in organizational cyber security and defense. Strategies for effective threat detection and mitigation are presented, with an emphasis on deep learning, artificial intelligence, and Internet of Things (IoT) technology. This book covers topics such as cyber security, threat intelligence, and behavior analysis, and is a useful resource for computer engineers, security professionals, business owners, government officials, data analysts, academicians, scientists, and researchers.

Decision Making and Security Risk Management for IoT Environments

Author : Wadii Boulila
Publisher : Springer Nature
ISBN 13 : 3031475909
Total Pages : 231 pages
Book Rating : 4.0/5 (314 download)

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Book Synopsis Decision Making and Security Risk Management for IoT Environments by : Wadii Boulila

Download or read book Decision Making and Security Risk Management for IoT Environments written by Wadii Boulila and published by Springer Nature. This book was released on with total page 231 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Machine Learning for Cyber Security

Author : Preeti Malik
Publisher : Walter de Gruyter GmbH & Co KG
ISBN 13 : 3110766760
Total Pages : 170 pages
Book Rating : 4.1/5 (17 download)

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Book Synopsis Machine Learning for Cyber Security by : Preeti Malik

Download or read book Machine Learning for Cyber Security written by Preeti Malik and published by Walter de Gruyter GmbH & Co KG. This book was released on 2022-12-05 with total page 170 pages. Available in PDF, EPUB and Kindle. Book excerpt: 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.

Deep Learning Techniques for IoT Security and Privacy

Author : Mohamed Abdel-Basset
Publisher : Springer Nature
ISBN 13 : 3030890252
Total Pages : 273 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Deep Learning Techniques for IoT Security and Privacy by : Mohamed Abdel-Basset

Download or read book Deep Learning Techniques for IoT Security and Privacy written by Mohamed Abdel-Basset and published by Springer Nature. This book was released on 2021-12-05 with total page 273 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book states that the major aim audience are people who have some familiarity with Internet of things (IoT) but interested to get a comprehensive interpretation of the role of deep Learning in maintaining the security and privacy of IoT. A reader should be friendly with Python and the basics of machine learning and deep learning. Interpretation of statistics and probability theory will be a plus but is not certainly vital for identifying most of the book's material.

Leveraging Artificial Intelligence (AI) Competencies for Next-Generation Cybersecurity Solutions

Author : Pethuru Raj
Publisher : CRC Press
ISBN 13 : 1040026060
Total Pages : 580 pages
Book Rating : 4.0/5 (4 download)

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Book Synopsis Leveraging Artificial Intelligence (AI) Competencies for Next-Generation Cybersecurity Solutions by : Pethuru Raj

Download or read book Leveraging Artificial Intelligence (AI) Competencies for Next-Generation Cybersecurity Solutions written by Pethuru Raj and published by CRC Press. This book was released on 2024-11-22 with total page 580 pages. Available in PDF, EPUB and Kindle. Book excerpt: Modern enterprises are facing growing cybersecurity issues due to the massive volume of security-related data they generate over time. AI systems can be developed to resolve a range of these issues with comparative ease. This new book describes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help eliminate them. With chapters from industry and security experts, this volume discribes the various types of cybersecurity problems faced by businesses and how advanced AI algorithms and models can help elimintate them. With chapters from industry and security experts, this volume discusses the many new and emerging AI technologies and approaches that can be harnessed to combat cyberattacks, including big data analytics techniques, deep neural networks, cloud computer networks, convolutional neural networks, IoT edge devices, machine learning approaches, deep learning, blockchain technology, convolutional neural networks, and more. Some unique features of this book include: Detailed overview of various security analytics techniques and tools Comprehensive descriptions of the emerging and evolving aspects of artificial intelligence (AI) technologies Industry case studies for practical comprehension and application This book, Leveraging the Artificial Intelligence Competencies for Next-Generation Cybersecurity Solutions, illustrates how AI is a futuristic and flexible technology that can be effectively used for tackling the growing menace of cybercriminals. It clearly demystifies the unique contributions of AI algorithms, models, frameworks, and libraries in nullifying the cyberattacks. The volume will be a valuable resource for research students, scholars, academic professors, business executives, security architects, and consultants in the IT industry.

Privacy, Security And Forensics in The Internet of Things (IoT)

Author : Reza Montasari
Publisher : Springer Nature
ISBN 13 : 3030912183
Total Pages : 220 pages
Book Rating : 4.0/5 (39 download)

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Book Synopsis Privacy, Security And Forensics in The Internet of Things (IoT) by : Reza Montasari

Download or read book Privacy, Security And Forensics in The Internet of Things (IoT) written by Reza Montasari and published by Springer Nature. This book was released on 2022-02-16 with total page 220 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book provides the most recent security, privacy, technical and legal challenges in the IoT environments. This book offers a wide range of theoretical and technical solutions to address these challenges. Topics covered in this book include; IoT, privacy, ethics and security, the use of machine learning algorithms in classifying malicious websites, investigation of cases involving cryptocurrency, the challenges police and law enforcement face in policing cyberspace, the use of the IoT in modern terrorism and violent extremism, the challenges of the IoT in view of industrial control systems, and the impact of social media platforms on radicalisation to terrorism and violent extremism. This book also focuses on the ethical design of the IoT and the large volumes of data being collected and processed in an attempt to understand individuals’ perceptions of data and trust. A particular emphasis is placed on data ownership and perceived rights online. It examines cyber security challenges associated with the IoT, by making use of Industrial Control Systems, using an example with practical real-time considerations. Furthermore, this book compares and analyses different machine learning techniques, i.e., Gaussian Process Classification, Decision Tree Classification, and Support Vector Classification, based on their ability to learn and detect the attributes of malicious web applications. The data is subjected to multiple steps of pre-processing including; data formatting, missing value replacement, scaling and principal component analysis. This book has a multidisciplinary approach. Researchers working within security, privacy, technical and legal challenges in the IoT environments and advanced-level students majoring in computer science will find this book useful as a reference. Professionals working within this related field will also want to purchase this book.

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)

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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.

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)

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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.

Blockchain and Machine Learning for IoT Security

Author : Mourade Azrour
Publisher : CRC Press
ISBN 13 : 100384488X
Total Pages : 164 pages
Book Rating : 4.0/5 (38 download)

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Book Synopsis Blockchain and Machine Learning for IoT Security by : Mourade Azrour

Download or read book Blockchain and Machine Learning for IoT Security written by Mourade Azrour and published by CRC Press. This book was released on 2024-02-09 with total page 164 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Internet of Things (IoT) involves physical devices, cars, household appliances, and any other physical appliance equipped with sensors, software, and network connections to gather and communicate data. Nowadays, this technology is embedded in everything from simple smart devices, to wearable equipment, to complex industrial machinery and transportation infrastructures. On the other hand, IoT equipment has been designed without considering security issues. Consequently, there are many challenges in terms of protection against IoT threats, which can lead to distressing situations. In fact, unlike other technological solutions, there are few standards and guidelines governing the protection of IoT technology. Moreover, few users are aware of the risks associated with IoT systems. Hence, Blockchain and Machine Learning for IoT Security discusses various recent techniques and solutions related to IoT deployment, especially security and privacy. This book addresses a variety of subjects, including a comprehensive overview of the IoT, and covers in detail the security challenges at each layer by considering how both the architecture and underlying technologies are employed. As acknowledged experts in the field, the authors provide remediation solutions for impaired security, as well as mitigation methods, and offer both prevention and improvement suggestions. Key Features: Offers a unique perspective on IoT security by introducing Machine Learning and Blockchain solutions Presents a well-rounded overview of the most recent advances in IoT security and privacy Discusses practical solutions and real-world cases for IoT solutions in various areas Provides solutions for securing IoT against various threats Discuses Blockchain technology as a solution for IoT This book is designed to provide all the necessary knowledge for young researchers, academics, and industry professionals who want to understand the advantages of artificial intelligence technology, machine learning, data analysis methodology, and Blockchain for securing IoT technologies.

Securing IoT and Big Data

Author : Vijayalakshmi Saravanan
Publisher : CRC Press
ISBN 13 : 1000258513
Total Pages : 191 pages
Book Rating : 4.0/5 (2 download)

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Book Synopsis Securing IoT and Big Data by : Vijayalakshmi Saravanan

Download or read book Securing IoT and Big Data written by Vijayalakshmi Saravanan and published by CRC Press. This book was released on 2020-12-16 with total page 191 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book covers IoT and Big Data from a technical and business point of view. The book explains the design principles, algorithms, technical knowledge, and marketing for IoT systems. It emphasizes applications of big data and IoT. It includes scientific algorithms and key techniques for fusion of both areas. Real case applications from different industries are offering to facilitate ease of understanding the approach. The book goes on to address the significance of security algorithms in combing IoT and big data which is currently evolving in communication technologies. The book is written for researchers, professionals, and academicians from interdisciplinary and transdisciplinary areas. The readers will get an opportunity to know the conceptual ideas with step-by-step pragmatic examples which makes ease of understanding no matter the level of the reader.