Quan Z. Sheng – författare

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.

The text highlights a comprehensive survey that focuses on all security aspects and challenges facing the Internet of Things systems, including outsourcing techniques for partial computations on edge or cloud while presenting case studies to map security challenges. It further covers three security aspects including Internet of Things device identification and authentication, network traffic intrusion detection, and executable malware files detection.This book:Presents a security framework model design named Behavioral Network Traffic Identification and Novelty Anomaly Detection for the IoT InfrastructuresHighlights recent advancements in machine learning, deep learning, and networking standards to boost Internet of Things securityBuilds a near real-time solution for identifying Internet of Things devices connecting to a network using their network traffic traces and providing them with sufficient access privilegesDevelops a robust framework for detecting IoT anomalous network trafficCovers an anti-malware solution for detecting malware targeting embedded devicesIt will serve as an ideal text for senior undergraduate and graduate students, and professionals in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

This book delves into the critical realm of trust management within the Internet of Vehicles (IOV) networks, exploring its multifaceted implications on safety and security which forms part of the intelligent transportation system domain.IoV emerges as a powerful convergence, seamlessly amalgamating the Internet of Things (IoT) and the intelligent transportation systems (ITS). This is crucial not only for safety-critical applications but is also an indispensable resource for non-safety applications and efficient traffic flows. While this paradigm holds numerous advantages, the existence of malicious entities and the potential spread of harmful information within the network not only impairs its performance but also presents a danger to both passengers and pedestrians. Exploring the complexities arising from dynamicity and malicious actors, this book focuses primarily on modern trust management models designed to pinpoint and eradicate threats. This includes tackling the challenges regarding the quantification of trust attributes, corresponding weights of these attributes, and misbehavior detection threshold definition within the dynamic and distributed IoV environment.This will serve as an essential guide for industry professionals and researchers working in the areas of automotive systems and transportation networks. Additionally, it will also be useful as a supplementary text for students enrolled in courses covering cybersecurity, communication networks, and human factors in transportation.Sarah Ali Siddiqui is a CSIRO Early Research Career (CERC) Fellow in the Cyber Security Automation and Orchestration Team, Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia. Adnan Mahmood is a Lecturer in Computing – IoT and Networking at the School of Computing, Macquarie University, Sydney, Australia.Quan Z. (Michael) Sheng is a Distinguished Professor and Head of the School of Computing, at Macquarie University, Sydney, Australia.Hajime Suzuki is a Principal Research Scientist at the Cybersecurity & Quantum Systems Group, Software and Computational Systems Research Program, Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia.Wei Ni is a Principal Scientist at the Commonwealth Scientific and Industrial Research Organisation, a Technical Expert at Standards Australia, a Conjoint Pro-fessor at the University of New South Wales, an Adjunct Professor at the University of Technology Sydney, and an Honorary Professor at Macquarie University, Sydney, Australia.

This book delves into the critical realm of trust management within the Internet of Vehicles (IOV) networks, exploring its multifaceted implications on safety and security which forms part of the intelligent transportation system domain.IoV emerges as a powerful convergence, seamlessly amalgamating the Internet of Things (IoT) and the intelligent transportation systems (ITS). This is crucial not only for safety-critical applications but is also an indispensable resource for non-safety applications and efficient traffic flows. While this paradigm holds numerous advantages, the existence of malicious entities and the potential spread of harmful information within the network not only impairs its performance but also presents a danger to both passengers and pedestrians. Exploring the complexities arising from dynamicity and malicious actors, this book focuses primarily on modern trust management models designed to pinpoint and eradicate threats. This includes tackling the challenges regarding the quantification of trust attributes, corresponding weights of these attributes, and misbehavior detection threshold definition within the dynamic and distributed IoV environment.This will serve as an essential guide for industry professionals and researchers working in the areas of automotive systems and transportation networks. Additionally, it will also be useful as a supplementary text for students enrolled in courses covering cybersecurity, communication networks, and human factors in transportation.Sarah Ali Siddiqui is a CSIRO Early Research Career (CERC) Fellow in the Cyber Security Automation and Orchestration Team, Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia. Adnan Mahmood is a Lecturer in Computing – IoT and Networking at the School of Computing, Macquarie University, Sydney, Australia.Quan Z. (Michael) Sheng is a Distinguished Professor and Head of the School of Computing, at Macquarie University, Sydney, Australia.Hajime Suzuki is a Principal Research Scientist at the Cybersecurity & Quantum Systems Group, Software and Computational Systems Research Program, Data61, Commonwealth Scientific and Industrial Research Organisation (CSIRO), Australia.Wei Ni is a Principal Scientist at the Commonwealth Scientific and Industrial Research Organisation, a Technical Expert at Standards Australia, a Conjoint Pro-fessor at the University of New South Wales, an Adjunct Professor at the University of Technology Sydney, and an Honorary Professor at Macquarie University, Sydney, Australia.

The text highlights a comprehensive survey that focuses on all security aspects and challenges facing the Internet of Things systems, including outsourcing techniques for partial computations on edge or cloud while presenting case studies to map security challenges. It further covers three security aspects including Internet of Things device identification and authentication, network traffic intrusion detection, and executable malware files detection.This book:Presents a security framework model design named Behavioral Network Traffic Identification and Novelty Anomaly Detection for the IoT InfrastructuresHighlights recent advancements in machine learning, deep learning, and networking standards to boost Internet of Things securityBuilds a near real-time solution for identifying Internet of Things devices connecting to a network using their network traffic traces and providing them with sufficient access privilegesDevelops a robust framework for detecting IoT anomalous network trafficCovers an anti-malware solution for detecting malware targeting embedded devicesIt will serve as an ideal text for senior undergraduate and graduate students, and professionals in the fields of electrical engineering, electronics and communication engineering, computer engineering, and information technology.

This book examines the uses and potential risks of location-based services (LBS) in the context of big data, with a focus on location privacy protection methods.The growth of the mobile Internet and the popularity of smart devices have spurred the development of LBS and related mobile applications. However, the misuse of sensitive location data could compromise the physical and communication security of associated devices and nodes, potentially leading to privacy breaches. This book explores the potential risks to the location privacy of mobile users in the context of big data applications. It discusses the latest methods and implications of location privacy from different perspectives. The author offers case studies of three applications: statistical disclosure and privacy protection of location-based big data using a centralized differential privacy model; a user location perturbation mechanism based on a localized differential privacy model; and terminal location perturbation using a geo-indistinguishability model. Linking recent developments in three-dimensional positioning and artificial intelligence, the book also predicts future trends and provides insights into research issues in location privacy.This title will be a valuable resource for researchers, students, and professionals interested in location-based services, privacy computing and protection, wireless network security, and big data security.

This book examines the uses and potential risks of location-based services (LBS) in the context of big data, with a focus on location privacy protection methods.The growth of the mobile Internet and the popularity of smart devices have spurred the development of LBS and related mobile applications. However, the misuse of sensitive location data could compromise the physical and communication security of associated devices and nodes, potentially leading to privacy breaches. This book explores the potential risks to the location privacy of mobile users in the context of big data applications. It discusses the latest methods and implications of location privacy from different perspectives. The author offers case studies of three applications: statistical disclosure and privacy protection of location-based big data using a centralized differential privacy model; a user location perturbation mechanism based on a localized differential privacy model; and terminal location perturbation using a geo-indistinguishability model. Linking recent developments in three-dimensional positioning and artificial intelligence, the book also predicts future trends and provides insights into research issues in location privacy.This title will be a valuable resource for researchers, students, and professionals interested in location-based services, privacy computing and protection, wireless network security, and big data security.

This book looks at conversational search in intelligent dialogue systems, as it investigates and addresses the challenges pertinent to effective context incorporation in conversational question answering (ConvQA). The authors explore the possibility of designing a scalable Conversational Question Answering Agent that can handle the challenges of incomplete/ambiguous questions, better able to relate to co-references to cope with the problems of effective weights and optimal threshold selection in vehicular networks. A fundamental emphasis is the understanding of ambiguous follow-up questions and the generation of contextual and question entities to fill in the missing information gaps. Key topics are studied, such as ‘hard history selection’ to filter out the context that is not relevant and performing a re-ranking of the selected turns based on their significance to answer the question as a part of the soft history selection process.This book aims to demonstrate that the history selection and modelling approaches proposed can effectively improve the performance of ConvQA models in different settings. The proposed models are compared with the state-of-the-art vis-à-vis different conversational datasets and provide new insights into conversational information retrieval. Through a systematic study of structured representations, entity-aware history selection, and open-domain passage retrieval using contrastive learning, this book presents a robust framework for advancing multi-turn QA systems.It is an essential resource for researchers, practitioners, and graduate students working at the intersection of NLP, dialogue systems, and intelligent information access.

With recent advances in radio-frequency identification (RFID) technology, sensor networks, and enhanced Web services, the original World Wide Web is continuing its evolution into what is being called the Web of Things and Services. Such a Web will support an ultimately interactive environment where everyday physical objects such as buildings, sidewalks, and commodities become recognizable, addressable, and even controllable via a mostly ubiquitous Web. This integration of the physical and virtual worlds will fundamentally impact the way we live and in doing so afford tremendous new business opportunities with great human benefit, such as support services to keep the elderly independent, and intelligent traffic management that will cut wasted hours from every day. More efficient supply chains, improved environmental monitoring, better access to health services … the list is endless.Enabling Context-Aware Web Services: Methods, Architectures, and Technologies compiles the newest developments and advances driving this new age forward. With contributions from leading researchers across the world this pioneering work bridges the gap between context-awareness and Web services. A comprehensive presentation of what’s already accomplished and what is possible, the chapters of this book are systematically organized into three major sections: Methods focuses on the principle of context awareness in Web services and various ways to model those services at the specification level. Architectures details the infrastructures, frameworks, and standards needed to build context-aware Web services. Technologies presents a cornucopia of techniques adapted from once isolated research areas including semantic Web, database, and artificial intelligence development, as well as formal methods being employed to improve the development of context-aware Web services.Researchers, engineers, entrepreneurs, and educators across any number of fields will find new ideas worth considering, jumping-off points for developing improved software and applications, and seeds for business ventures that efficiently deliver needed products, information, or services. The possibilities are as limitless as we dare to imagine.

While Computer Security is a broader term which incorporates technologies, protocols, standards and policies to ensure the security of the computing systems including the computer hardware, software and the information stored in it, Cyber Security is a specific, growing field to protect computer networks (offline and online) from unauthorized access, botnets, phishing scams, etc. Machine learning is a branch of Computer Science which enables computing machines to adopt new behaviors on the basis of observable and verifiable data and information. It can be applied to ensure the security of the computers and the information by detecting anomalies using data mining and other such techniques.This book will be an invaluable resource to understand the importance of machine learning and data mining in establishing computer and cyber security. It emphasizes important security aspects associated with computer and cyber security along with the analysis of machine learning and data mining based solutions. The book also highlights the future research domains in which these solutions can be applied. Furthermore, it caters to the needs of IT professionals, researchers, faculty members, scientists, graduate students, research scholars and software developers who seek to carry out research and develop combating solutions in the area of cyber security using machine learning based approaches. It is an extensive source of information for the readers belonging to the field of Computer Science and Engineering, and Cyber Security professionals.Key Features: This book contains examples and illustrations to demonstrate the principles, algorithms, challenges and applications of machine learning and data mining for computer and cyber security. It showcases important security aspects and current trends in the field. It provides an insight of the future research directions in the field. Contents of this book help to prepare the students for exercising better defense in terms of understanding the motivation of the attackers and how to deal with and mitigate the situation using machine learning based approaches in better manner.

Web services and Service-Oriented Computing (SOC) have become thriving areas of academic research, joint university/industry research projects, and novel IT products on the market. SOC is the computing paradigm that uses Web services as building blocks for the engineering of composite, distributed applications out of the reusable application logic encapsulated by Web services. Web services could be considered the best-known and most standardized technology in use today for distributed computing over the Internet.Web Services Foundations is the first installment of a two-book collection covering the state-of-the-art of both theoretical and practical aspects of Web services and SOC research. This book specifically focuses on the foundations of Web services and SOC and covers - among others - Web service composition, non-functional aspects of Web services, Web service selection and recommendation, and assisted Web service composition.The editors collect advanced topics in the second book of the collection, Advanced Web Services, (Springer, 2013). Both books together comprise approximately 1400 pages and are the result of an enormous community effort that involved more than 100 authors, comprising the world’s leading experts in this field.

Web services and Service-Oriented Computing (SOC) have become thriving areas of academic research, joint university/industry research projects, and novel IT products on the market. SOC is the computing paradigm that uses Web services as building blocks for the engineering of composite, distributed applications out of the reusable application logic encapsulated by Web services. Web services could be considered the best-known and most standardized technology in use today for distributed computing over the Internet. This book is the second installment of a two-book collection covering the state-of-the-art of both theoretical and practical aspects of Web services and SOC research and deployments. Advanced Web Services specifically focuses on advanced topics of Web services and SOC and covers topics including Web services transactions, security and trust, Web service management, real-world case studies, and novel perspectives and future directions. The editors present foundational topics in the first book of the collection, Web Services Foundations (Springer, 2013). Together, both books comprise approximately 1400 pages and are the result of an enormous community effort that involved more than 100 authors, comprising the world’s leading experts in this field.

Advanced Web Services specifically focuses on advanced topics of Web services and SOC and covers topics including Web services transactions, security and trust, Web service management, real-world case studies, and novel perspectives and future directions.

Web services and Service-Oriented Computing (SOC) have become thriving areas of academic research, joint university/industry research projects, and novel IT products on the market. SOC is the computing paradigm that uses Web services as building blocks for the engineering of composite, distributed applications out of the reusable application logic encapsulated by Web services. Web services could be considered the best-known and most standardized technology in use today for distributed computing over the Internet.Web Services Foundations is the first installment of a two-book collection covering the state-of-the-art of both theoretical and practical aspects of Web services and SOC research. This book specifically focuses on the foundations of Web services and SOC and covers - among others - Web service composition, non-functional aspects of Web services, Web service selection and recommendation, and assisted Web service composition.The editors collect advanced topics in the second book of the collection, Advanced Web Services, (Springer, 2013). Both books together comprise approximately 1400 pages and are the result of an enormous community effort that involved more than 100 authors, comprising the world’s leading experts in this field.

Their feature modelling approach eschews the knowledge requirement on both the querying languages and system.To extract knowledge from unstructured Web sources, the authors examine two kinds of Web sources containing unstructured data: the source code from Web repositories and the posts in programming question-answering communities.

This book constitutes revised papers from the eight International Workshops held at the 16th International Conference on Business Process Management, BPM 2018, in Sydney, Australia, in September 2018:BPI 2018: 14th International Workshop on Business Process Intelligence;BPMS2 2018: 11th Workshop on Social and Human Aspects of Business Process Management;‐ PODS4H 2018: 1st International Workshop on Process-Oriented Data Science for Healthcare;AI4BPM 2018: 1st International Workshop on Artificial Intelligence for Business Process Management; CCBPM 2018: 1st International Workshop on Emerging Computing Paradigms and Context in Business Process Management;BP-Meet-IoT / PQ 2018: Joint Business Processes Meet the Internet-of-Things and Process Querying Workshop;DeHMiMoP 2018: 1st Declarative/Decision/Hybrid Mining and Modelling for Business Processes Workshop;REBM /EdForum 2018: Joint Requirements Engineering and Business Process Management Workshop and Education ForumThe 45 full papers presented in this volume were carefully reviewed and selected from 90 submissions.

This book constitutes revised selected papers from the International Workshop on Data Quality and Trust in Big Data, QUAT 2018, which was held in conjunction with the International Conference on Web Information Systems Engineering, WISE 2018, in Dubai, UAE, in November 2018.

This book, at first, explores the evolution of the IoT to SIoT and offers a comprehensive understanding of SIoT and trust management vis-à-vis SIoT.

This book, at first, explores the evolution of the IoT to SIoT and offers a comprehensive understanding of SIoT and trust management vis-à-vis SIoT. It subsequently envisages trust quantification models by employing key SIoT-specific trust features, including SIoT relationships (e.g., friendships, working relationships, and community-of-interest), direct observations, and indirect observations, to augment the idea of trust quantification of a SIoT object. Furthermore, diverse trust aggregation techniques, i.e., conventional weighted sum, machine learning, and artificial neural networks, are proposed so as to address the challenges of the trust aggregation. Finally, the book outlines the future research directions for emphasizing the importance of trustworthiness management in the evolving notion of the SIoT.

This book provides a comprehensive overview of the latest research progress in addressing the challenges faced by the support for aging population. It covers a broad spectrum of technologies, including the Internet of Things (IoT) and Artificial Intelligence (AI), that are pivotal in supporting older people in their daily lives. The book delves into various domains such as human activity recognition, indoor localization, cognitive activity recognition, and AI-empowered health and identity management solutions. Additionally, it explores the integration of brain-computer interfaces and the development of intent-aware interactive robot-assisted systems, offering insights into how these cutting-edge technologies can be harnessed to enhance the quality of life for the older population.This book is a collection of 15 chapters that summarize the decade-long research activities and results from the authors on tackling smart aging challenges. The book provides a detailed exposition of the latest research activities and technological breakthroughs in smart aging, and aims to bridge the gap between advanced technologies and their practical applications in enhancing the daily lives of older people. From this book, readers will be able to gain not only a wide range of topics and the corresponding technological advancements, but also a comprehensive understanding of how various technologies can be harmonized to create effective and practical smart aging solutions.

This book constitutes the thoroughly refereed post-proceedings of the seven workshops and the PhD Symposium that were co-located with the 13th International Conference on Web Engineering, ICWE 2013, held in Aalborg, Denmark, in July 2013. The papers cover research in topics such as social data management; cloud service engineering; agile web development and quality management in web engineering.

This book describes the design and implementation of Cloud Armor, a novel approach for credibility-based trust management and automatic discovery of cloud services in distributed and highly dynamic environments. This book also helps cloud users to understand the difficulties of establishing trust in cloud computing and the best criteria for selecting a service cloud. The techniques have been validated by a prototype system implementation and experimental studies using a collection of real world trust feedbacks on cloud services.The authors present the design and implementation of a novel protocol that preserves the consumers’ privacy, an adaptive and robust credibility model, a scalable availability model that relies on a decentralized architecture, and a cloud service crawler engine for automatic cloud services discovery. This book also analyzes results from a performance study on a number of open research issues for trust management in cloud environments including distribution of providers, geographic location and languages. These open research issues illustrate both an overview of the current state of cloud computing and potential future directions for the field.Trust Management in Cloud Services contains both theoretical and applied computing research, making it an ideal reference or secondary text book to both academic and industry professionals interested in cloud services. Advanced-level students in computer science and electrical engineering will also find the content valuable.

This book describes the design and implementation of Cloud Armor, a novel approach for credibility-based trust management and automatic discovery of cloud services in distributed and highly dynamic environments. This book also helps cloud users to understand the difficulties of establishing trust in cloud computing and the best criteria for selecting a service cloud. The techniques have been validated by a prototype system implementation and experimental studies using a collection of real world trust feedbacks on cloud services.The authors present the design and implementation of a novel protocol that preserves the consumers’ privacy, an adaptive and robust credibility model, a scalable availability model that relies on a decentralized architecture, and a cloud service crawler engine for automatic cloud services discovery. This book also analyzes results from a performance study on a number of open research issues for trust management in cloud environments including distribution of providers, geographic location and languages. These open research issues illustrate both an overview of the current state of cloud computing and potential future directions for the field.Trust Management in Cloud Services contains both theoretical and applied computing research, making it an ideal reference or secondary text book to both academic and industry professionals interested in cloud services. Advanced-level students in computer science and electrical engineering will also find the content valuable.

This book constitutes the proceedings of the 14th International Conference on Service-Oriented Computing, ICSOC 2016, held in Banff, AB, Canada, in October 2016. The 30 full papers presented together with 18 short papers and 8 industrial papers in this volume were carefully reviewed and selected from 137 submissions.The selected papers covered important topics in the area of service-oriented computing, including foundational issues on service discovery and service-systems design, business process modelling and management, economics of service-systems engineering, as well as services on the cloud, social networks, the Internet of Things (IoT), and data analytics.

The selected papers covered a wide variety of important topics in the area of data mining, including parallel and distributed data mining algorithms, mining on data streams, graph mining, spatial data mining, multimedia data mining, Web mining, the Internet of Things, health informatics, and biomedical data mining.

Their feature modelling approach eschews the knowledge requirement on both the querying languages and system.To extract knowledge from unstructured Web sources, the authors examine two kinds of Web sources containing unstructured data: the source code from Web repositories and the posts in programming question-answering communities.

This book constitutes the proceedings of the 6th International Conference on Web Information Systems Engineering, WISE 2005, held in New York, NY, USA, in November 2005.The 30 revised full papers and 20 revised short papers presented together with 18 poster papers were carefully reviewed and selected from 259 submissions. The papers are organized in topical sections on Web mining, Web information retrieval, metadata management, ontology and semantic Web, XML, Web service method, Web service structure, collaborative methodology, P2P, ubiquitous and mobile, document retrieval applications, Web services and e-commerce, recommendation and Web information extraction, P2P, grid and distributed management, and advanced issues. The presentation is rounded off by 14 industrial papers and the abstracts of 4 tutorial sessions.

This book constitutes the joint refereed proceedings of the three workshops held in conjunction with the 6th International Conference on Web Information Systems Engineering, WISE 2005, in New York, NY, USA, in November 2005.A total of 47 papers were submitted to the three workshops, and 28 revised full papers were carefully selected for presentation. The workshop on Web Information Systems Quality (WISQ 2005) - discussing and disseminating research on the quality of WIS and Web services from a holistic point of view - included 7 papers out of 12 submissions. The workshop on Web-based Learning (WBL 2005) accounted for 10 papers from 14 papers submitted - organized in topical sections on tools, models, and innovative applications. The workshop on Scalable Semantic Web Knowledge Base Systems (SSWS 2005) included 11 presentations selected from 21 submissions. Topics addressed are scalable repository and reasoning services, practical Semantic Web applications, query handling and optimization techniques.

Are you an engineer or a researcher developing RFID systems? Are you a manager considering deploying RFID-based applications? If so, this book is for you. Covering modern RFID systems, the challenges to RFID implementation are addressed using specific industrial research examples and common integration issues. The primary focus is on answering questions surrounding building scalable global Internet-based RFID networks. Key topics include RFID data management, RFID data processing and integration, Real-Time Locating Systems (RTLS) and sensors. The book considers the challenges of and solutions to building and exploiting global networks to guarantee one of the most important business drivers for modern RFID technology: traceability. The authors have drawn together RFID applications from the retail supply chain, asset and product lifecycle management, anti-counterfeiting and cold chain management to explore how global traceability networks can be created using RFID and sensor technologies. They present insights from world’s leading research laboratories.