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This Volume presents the selected papers from the 5 Parallel Symposiums of the 2014 Fourth World Congress on Information and Communication Technologies (WICT 2014) held in Malacca, Malaysia. The theme of WICT 2014 'Innovating ICT for Social Revolutions'. WICT 2014 is Co-Organized by Machine Intelligence Research Labs (MIR Labs), USA and Universiti Teknikal Malaysia Melaka, Malaysia. WICT 2014 is technically co-sponsored by IEEE Systems, Man & Cybernetics Society Malaysia and Spain Chapters and Technically Supported by IEEE Systems Man and Cybernetics Society, Technical Committee on Soft Computing.
Book Synopsis Pattern Analysis, Intelligent Security and the Internet of Things by : Ajith Abraham
Download or read book Pattern Analysis, Intelligent Security and the Internet of Things written by Ajith Abraham and published by Springer. This book was released on 2015-06-20 with total page 356 pages. Available in PDF, EPUB and Kindle. Book excerpt: This Volume presents the selected papers from the 5 Parallel Symposiums of the 2014 Fourth World Congress on Information and Communication Technologies (WICT 2014) held in Malacca, Malaysia. The theme of WICT 2014 'Innovating ICT for Social Revolutions'. WICT 2014 is Co-Organized by Machine Intelligence Research Labs (MIR Labs), USA and Universiti Teknikal Malaysia Melaka, Malaysia. WICT 2014 is technically co-sponsored by IEEE Systems, Man & Cybernetics Society Malaysia and Spain Chapters and Technically Supported by IEEE Systems Man and Cybernetics Society, Technical Committee on Soft Computing.
"The reference book will show the depth of Darkweb Environment by highlighting the Attackers techniques, crawling of hidden contents, Intrusion detection using advance algorithms, TOR Network structure, Memex search engine indexing of anonymous contents at Online Social Network, and more"--
Book Synopsis Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence by : Romil Rawat
Download or read book Dark Web Pattern Recognition and Crime Analysis Using Machine Intelligence written by Romil Rawat and published by Information Science Reference. This book was released on 2022 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: "The reference book will show the depth of Darkweb Environment by highlighting the Attackers techniques, crawling of hidden contents, Intrusion detection using advance algorithms, TOR Network structure, Memex search engine indexing of anonymous contents at Online Social Network, and more"--
In recent years, the need for smart equipment has increased exponentially with the upsurge in technological advances. To work to their fullest capacity, these devices need to be able to communicate with other devices in their network to exchange information and receive instructions. Computational Intelligence in the Internet of Things is an essential reference source that provides relevant theoretical frameworks and the latest empirical research findings in the area of computational intelligence and the Internet of Things. Featuring research on topics such as data analytics, machine learning, and neural networks, this book is ideally designed for IT specialists, managers, professionals, researchers, and academicians.
Book Synopsis Computational Intelligence in the Internet of Things by : Purnomo, Hindriyanto Dwi
Download or read book Computational Intelligence in the Internet of Things written by Purnomo, Hindriyanto Dwi and published by IGI Global. This book was released on 2019-03-15 with total page 342 pages. Available in PDF, EPUB and Kindle. Book excerpt: In recent years, the need for smart equipment has increased exponentially with the upsurge in technological advances. To work to their fullest capacity, these devices need to be able to communicate with other devices in their network to exchange information and receive instructions. Computational Intelligence in the Internet of Things is an essential reference source that provides relevant theoretical frameworks and the latest empirical research findings in the area of computational intelligence and the Internet of Things. Featuring research on topics such as data analytics, machine learning, and neural networks, this book is ideally designed for IT specialists, managers, professionals, researchers, and academicians.
Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the role of blockchain in all possible facets of IoT security. Furthermore, it investigates the security and privacy issues associated with various IoT systems along with exploring various machine learning-based IoT security solutions. This book brings together state-of-the-art innovations, research activities (both in academia and in industry), and the corresponding standardization impacts of 5G as well. Aimed at graduate students, researchers in computer science and engineering, communication networking, IoT, machine learning and pattern recognition, this book Showcases the basics of both IoT and various security paradigms supporting IoT, including Blockchain Explores various machine learning-based IoT security solutions and highlights the importance of IoT for industries and smart cities Presents various competitive technologies of Blockchain, especially concerned with IoT security Provides insights into the taxonomy of challenges, issues, and research directions in IoT-based applications Includes examples and illustrations to effectively demonstrate the principles, algorithm, applications, and practices of security in the IoT environment
Book Synopsis IoT Security Paradigms and Applications by : Sudhir Kumar Sharma
Download or read book IoT Security Paradigms and Applications written by Sudhir Kumar Sharma and published by CRC Press. This book was released on 2020-10-07 with total page 338 pages. Available in PDF, EPUB and Kindle. Book excerpt: Integration of IoT (Internet of Things) with big data and cloud computing has brought forward numerous advantages and challenges such as data analytics, integration, and storage. This book highlights these challenges and provides an integrating framework for these technologies, illustrating the role of blockchain in all possible facets of IoT security. Furthermore, it investigates the security and privacy issues associated with various IoT systems along with exploring various machine learning-based IoT security solutions. This book brings together state-of-the-art innovations, research activities (both in academia and in industry), and the corresponding standardization impacts of 5G as well. Aimed at graduate students, researchers in computer science and engineering, communication networking, IoT, machine learning and pattern recognition, this book Showcases the basics of both IoT and various security paradigms supporting IoT, including Blockchain Explores various machine learning-based IoT security solutions and highlights the importance of IoT for industries and smart cities Presents various competitive technologies of Blockchain, especially concerned with IoT security Provides insights into the taxonomy of challenges, issues, and research directions in IoT-based applications Includes examples and illustrations to effectively demonstrate the principles, algorithm, applications, and practices of security in the IoT environment
This handbook provides an overarching view of cyber security and digital forensic challenges related to big data and IoT environment, prior to reviewing existing data mining solutions and their potential application in big data context, and existing authentication and access control for IoT devices. An IoT access control scheme and an IoT forensic framework is also presented in this book, and it explains how the IoT forensic framework can be used to guide investigation of a popular cloud storage service. A distributed file system forensic approach is also presented, which is used to guide the investigation of Ceph. Minecraft, a Massively Multiplayer Online Game, and the Hadoop distributed file system environment are also forensically studied and their findings reported in this book. A forensic IoT source camera identification algorithm is introduced, which uses the camera's sensor pattern noise from the captured image. In addition to the IoT access control and forensic frameworks, this handbook covers a cyber defense triage process for nine advanced persistent threat (APT) groups targeting IoT infrastructure, namely: APT1, Molerats, Silent Chollima, Shell Crew, NetTraveler, ProjectSauron, CopyKittens, Volatile Cedar and Transparent Tribe. The characteristics of remote-controlled real-world Trojans using the Cyber Kill Chain are also examined. It introduces a method to leverage different crashes discovered from two fuzzing approaches, which can be used to enhance the effectiveness of fuzzers. Cloud computing is also often associated with IoT and big data (e.g., cloud-enabled IoT systems), and hence a survey of the cloud security literature and a survey of botnet detection approaches are presented in the book. Finally, game security solutions are studied and explained how one may circumvent such solutions. This handbook targets the security, privacy and forensics research community, and big data research community, including policy makers and government agencies, public and private organizations policy makers. Undergraduate and postgraduate students enrolled in cyber security and forensic programs will also find this handbook useful as a reference.
Book Synopsis Handbook of Big Data and IoT Security by : Ali Dehghantanha
Download or read book Handbook of Big Data and IoT Security written by Ali Dehghantanha and published by Springer. This book was released on 2019-03-22 with total page 384 pages. Available in PDF, EPUB and Kindle. Book excerpt: This handbook provides an overarching view of cyber security and digital forensic challenges related to big data and IoT environment, prior to reviewing existing data mining solutions and their potential application in big data context, and existing authentication and access control for IoT devices. An IoT access control scheme and an IoT forensic framework is also presented in this book, and it explains how the IoT forensic framework can be used to guide investigation of a popular cloud storage service. A distributed file system forensic approach is also presented, which is used to guide the investigation of Ceph. Minecraft, a Massively Multiplayer Online Game, and the Hadoop distributed file system environment are also forensically studied and their findings reported in this book. A forensic IoT source camera identification algorithm is introduced, which uses the camera's sensor pattern noise from the captured image. In addition to the IoT access control and forensic frameworks, this handbook covers a cyber defense triage process for nine advanced persistent threat (APT) groups targeting IoT infrastructure, namely: APT1, Molerats, Silent Chollima, Shell Crew, NetTraveler, ProjectSauron, CopyKittens, Volatile Cedar and Transparent Tribe. The characteristics of remote-controlled real-world Trojans using the Cyber Kill Chain are also examined. It introduces a method to leverage different crashes discovered from two fuzzing approaches, which can be used to enhance the effectiveness of fuzzers. Cloud computing is also often associated with IoT and big data (e.g., cloud-enabled IoT systems), and hence a survey of the cloud security literature and a survey of botnet detection approaches are presented in the book. Finally, game security solutions are studied and explained how one may circumvent such solutions. This handbook targets the security, privacy and forensics research community, and big data research community, including policy makers and government agencies, public and private organizations policy makers. Undergraduate and postgraduate students enrolled in cyber security and forensic programs will also find this handbook useful as a reference.
Presents recent significant and rapid development in the field of 2D and 3D image analysis 2D and 3D Image Analysis by Moments, is a unique compendium of moment-based image analysis which includes traditional methods and also reflects the latest development of the field. The book presents a survey of 2D and 3D moment invariants with respect to similarity and affine spatial transformations and to image blurring and smoothing by various filters. The book comprehensively describes the mathematical background and theorems about the invariants but a large part is also devoted to practical usage of moments. Applications from various fields of computer vision, remote sensing, medical imaging, image retrieval, watermarking, and forensic analysis are demonstrated. Attention is also paid to efficient algorithms of moment computation. Key features: Presents a systematic overview of moment-based features used in 2D and 3D image analysis. Demonstrates invariant properties of moments with respect to various spatial and intensity transformations. Reviews and compares several orthogonal polynomials and respective moments. Describes efficient numerical algorithms for moment computation. It is a "classroom ready" textbook with a self-contained introduction to classifier design. The accompanying website contains around 300 lecture slides, Matlab codes, complete lists of the invariants, test images, and other supplementary material. 2D and 3D Image Analysis by Moments, is ideal for mathematicians, computer scientists, engineers, software developers, and Ph.D students involved in image analysis and recognition. Due to the addition of two introductory chapters on classifier design, the book may also serve as a self-contained textbook for graduate university courses on object recognition.
Book Synopsis 2D and 3D Image Analysis by Moments by : Jan Flusser
Download or read book 2D and 3D Image Analysis by Moments written by Jan Flusser and published by John Wiley & Sons. This book was released on 2016-11-15 with total page 560 pages. Available in PDF, EPUB and Kindle. Book excerpt: Presents recent significant and rapid development in the field of 2D and 3D image analysis 2D and 3D Image Analysis by Moments, is a unique compendium of moment-based image analysis which includes traditional methods and also reflects the latest development of the field. The book presents a survey of 2D and 3D moment invariants with respect to similarity and affine spatial transformations and to image blurring and smoothing by various filters. The book comprehensively describes the mathematical background and theorems about the invariants but a large part is also devoted to practical usage of moments. Applications from various fields of computer vision, remote sensing, medical imaging, image retrieval, watermarking, and forensic analysis are demonstrated. Attention is also paid to efficient algorithms of moment computation. Key features: Presents a systematic overview of moment-based features used in 2D and 3D image analysis. Demonstrates invariant properties of moments with respect to various spatial and intensity transformations. Reviews and compares several orthogonal polynomials and respective moments. Describes efficient numerical algorithms for moment computation. It is a "classroom ready" textbook with a self-contained introduction to classifier design. The accompanying website contains around 300 lecture slides, Matlab codes, complete lists of the invariants, test images, and other supplementary material. 2D and 3D Image Analysis by Moments, is ideal for mathematicians, computer scientists, engineers, software developers, and Ph.D students involved in image analysis and recognition. Due to the addition of two introductory chapters on classifier design, the book may also serve as a self-contained textbook for graduate university courses on object recognition.
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.
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.
Artificial Intelligence to Solve Pervasive Internet of Things Issues discusses standards and technologies and wide-ranging technology areas and their applications and challenges, including discussions on architectures, frameworks, applications, best practices, methods and techniques required for integrating AI to resolve IoT issues. Chapters also provide step-by-step measures, practices and solutions to tackle vital decision-making and practical issues affecting IoT technology, including autonomous devices and computerized systems. Such issues range from adopting, mitigating, maintaining, modernizing and protecting AI and IoT infrastructure components such as scalability, sustainability, latency, system decentralization and maintainability. The book enables readers to explore, discover and implement new solutions for integrating AI to solve IoT issues. Resolving these issues will help readers address many real-world applications in areas such as scientific research, healthcare, defense, aeronautics, engineering, social media, and many others. Discusses intelligent techniques for the implementation of Artificial Intelligence in Internet of Things Prepared for researchers and specialists who are interested in the use and integration of IoT and Artificial Intelligence technologies
Book Synopsis Artificial Intelligence to Solve Pervasive Internet of Things Issues by : Gurjit Kaur
Download or read book Artificial Intelligence to Solve Pervasive Internet of Things Issues written by Gurjit Kaur and published by Academic Press. This book was released on 2020-11-18 with total page 430 pages. Available in PDF, EPUB and Kindle. Book excerpt: Artificial Intelligence to Solve Pervasive Internet of Things Issues discusses standards and technologies and wide-ranging technology areas and their applications and challenges, including discussions on architectures, frameworks, applications, best practices, methods and techniques required for integrating AI to resolve IoT issues. Chapters also provide step-by-step measures, practices and solutions to tackle vital decision-making and practical issues affecting IoT technology, including autonomous devices and computerized systems. Such issues range from adopting, mitigating, maintaining, modernizing and protecting AI and IoT infrastructure components such as scalability, sustainability, latency, system decentralization and maintainability. The book enables readers to explore, discover and implement new solutions for integrating AI to solve IoT issues. Resolving these issues will help readers address many real-world applications in areas such as scientific research, healthcare, defense, aeronautics, engineering, social media, and many others. Discusses intelligent techniques for the implementation of Artificial Intelligence in Internet of Things Prepared for researchers and specialists who are interested in the use and integration of IoT and Artificial Intelligence technologies
This volume constitutes the refereed proceedings of the Third International Conference on Computational Intelligence, Security and Internet of Things, ICCISIoT 2020, held in Agartala, India, in December 2020. Due to the COVID-19 pandemic the conference was held online. The 23 full papers and 4 short papers were carefully reviewed and selected from 113 submissions. The papers are organised according to the following topics: computational intelligence, security, and internet of things.
Book Synopsis Trends in Computational Intelligence, Security and Internet of Things by : Nirmalya Kar
Download or read book Trends in Computational Intelligence, Security and Internet of Things written by Nirmalya Kar and published by Springer Nature. This book was released on 2020-12-29 with total page 339 pages. Available in PDF, EPUB and Kindle. Book excerpt: This volume constitutes the refereed proceedings of the Third International Conference on Computational Intelligence, Security and Internet of Things, ICCISIoT 2020, held in Agartala, India, in December 2020. Due to the COVID-19 pandemic the conference was held online. The 23 full papers and 4 short papers were carefully reviewed and selected from 113 submissions. The papers are organised according to the following topics: computational intelligence, security, and internet of things.
This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions. Focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives; Promotes an exchange of research across disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures; Features case studies emphasizing social and research perspectives on cyber-physical systems, data analytics, intelligence and security.
Book Synopsis Intelligent Internet of Things for Healthcare and Industry by : Uttam Ghosh
Download or read book Intelligent Internet of Things for Healthcare and Industry written by Uttam Ghosh and published by Springer Nature. This book was released on 2022 with total page 388 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book promotes and facilitates exchanges of research knowledge and findings across different disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures. This book is focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives. The data analytics discussed are relevant for healthcare and industry to meet many technical challenges and issues that need to be addressed to realize this potential. The IoT discussed helps to design and develop the intelligent medical and industry solutions assisted by data analytics and machine learning. At the end of every chapter readers are encouraged to check their understanding by means of brainstorming summary, discussion, exercises and solutions. Focused on the emerging trends, strategies, and applications of IoT in both healthcare and industry data analytics perspectives; Promotes an exchange of research across disciplines on the design and investigation of machine learning-based data analytics of IoT infrastructures; Features case studies emphasizing social and research perspectives on cyber-physical systems, data analytics, intelligence and security.
