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Author: Xin Liu
Publisher: CRC Press
ISBN: 1482226677
Category : Computers
Languages : en
Pages : 227
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Book Description
Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book:Explains
Author: Xin Liu
Publisher: CRC Press
ISBN: 1482226677
Category : Computers
Languages : en
Pages : 227
Get Book Here
Book Description
Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book:Explains
Author: Xin Liu
Publisher: CRC Press
ISBN: 1482226669
Category : Computers
Languages : en
Pages : 234
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Book Description
Computational Trust Models and Machine Learning provides a detailed introduction to the concept of trust and its application in various computer science areas, including multi-agent systems, online social networks, and communication systems. Identifying trust modeling challenges that cannot be addressed by traditional approaches, this book: Explains how reputation-based systems are used to determine trust in diverse online communities Describes how machine learning techniques are employed to build robust reputation systems Explores two distinctive approaches to determining credibility of resources—one where the human role is implicit, and one that leverages human input explicitly Shows how decision support can be facilitated by computational trust models Discusses collaborative filtering-based trust aware recommendation systems Defines a framework for translating a trust modeling problem into a learning problem Investigates the objectivity of human feedback, emphasizing the need to filter out outlying opinions Computational Trust Models and Machine Learning effectively demonstrates how novel machine learning techniques can improve the accuracy of trust assessment.
Author: Christiano Castelfranchi
Publisher: John Wiley & Sons
ISBN: 9780470519844
Category : Technology & Engineering
Languages : en
Pages : 386
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Book Description
This book provides an introduction, discussion, and formal-based modelling of trust theory and its applications in agent-based systems This book gives an accessible explanation of the importance of trust in human interaction and, in general, in autonomous cognitive agents including autonomous technologies. The authors explain the concepts of trust, and describe a principled, general theory of trust grounded on cognitive, cultural, institutional, technical, and normative solutions. This provides a strong base for the author’s discussion of role of trust in agent-based systems supporting human-computer interaction and distributed and virtual organizations or markets (multi-agent systems). Key Features: Provides an accessible introduction to trust, and its importance and applications in agent-based systems Proposes a principled, general theory of trust grounding on cognitive, cultural, institutional, technical, and normative solutions. Offers a clear, intuitive approach, and systematic integration of relevant issues Explains the dynamics of trust, and the relationship between trust and security Offers operational definitions and models directly applicable both in technical and experimental domains Includes a critical examination of trust models in economics, philosophy, psychology, sociology, and AI This book will be a valuable reference for researchers and advanced students focused on information and communication technologies (computer science, artificial intelligence, organizational sciences, and knowledge management etc.), as well as Web-site and robotics designers, and for scholars working on human, social, and cultural aspects of technology. Professionals of ecommerce systems and peer-to-peer systems will also find this text of interest.
Author: Young Ae Kim
Publisher:
ISBN:
Category :
Languages : en
Pages : 0
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Book Description
With the proliferation of online communities and Person-to-Person (P2P) online service markets, the deployment of knowledge, skills, experiences and user generated contents services are generally facilitated among service users and service providers. In online service markets where well-established intermediaries are often eliminated, the success of social interactions for service exchange among completely unknown users depends on 'trust' of a service user for a service provider. Therefore, providing a satisfactory trust model to evaluate the quality of services and to recommend personalized trustworthy service providers is vital for a successful online community and P2P online service market. However, finding trustworthy service providers for each individual user is challenging because of the lack of direct experiences and the subjective property of trust. In order to resolve the challenges, current research on trust prediction strongly relies on a web of trust, which is directly collected from users. However, the web of trust is not always available in online communities and, even when it is available, it is often too sparse to accurately predict the trust value between two unacquainted people. In this paper, we propose a computational trust model to predict trust connectivity based on service providers' expertise (local trust from direct experiences and a reputation) and service users' affinity for certain contexts (topics). The approach used item rating data that is available and much more dense than direct trust data. In experiments with a real-world dataset, we show that our model can predict trust connectivity with a high degree of accuracy. The proposed computational trust framework can be applied to any type of online communities or P2P online service markets with a rating system.
Author: Jiliang Tang
Publisher: Morgan & Claypool Publishers
ISBN: 1627054057
Category : Computers
Languages : en
Pages : 129
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Book Description
Social media greatly enables people to participate in online activities and shatters the barrier for online users to create and share information at any place at any time. However, the explosion of user-generated content poses novel challenges for online users to find relevant information, or,
Author: Jeffrey J. P. Tsai
Publisher: Springer Science & Business Media
ISBN: 0387887350
Category : Computers
Languages : en
Pages : 367
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Book Description
Many networked computer systems are far too vulnerable to cyber attacks that can inhibit their functioning, corrupt important data, or expose private information. Not surprisingly, the field of cyber-based systems is a fertile ground where many tasks can be formulated as learning problems and approached in terms of machine learning algorithms. This book contains original materials by leading researchers in the area and covers applications of different machine learning methods in the reliability, security, performance, and privacy issues of cyber space. It enables readers to discover what types of learning methods are at their disposal, summarizing the state-of-the-practice in this significant area, and giving a classification of existing work. Those working in the field of cyber-based systems, including industrial managers, researchers, engineers, and graduate and senior undergraduate students will find this an indispensable guide in creating systems resistant to and tolerant of cyber attacks.
Author: Seifeddine Kramdi
Publisher:
ISBN:
Category :
Languages : en
Pages : 128
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Book Description
The concept of trust is a socio-cognitive concept that plays an important role in representing interactions within concurrent systems. When the complexity of a computational system and its unpredictability makes standard security solutions (commonly called hard security solutions) inapplicable, computational trust is one of the most useful concepts to design protocols of interaction. In this work, our main objective is to present a prospective survey of the field of study of computational trust. We will also present two trust models, based on logical formalisms, and show how they can be studied and used. While trying to stay general in our study, we use service-oriented architecture paradigm as a context of study when examples are needed. Our work is subdivided into three chapters. The first chapter presents a general view of the computational trust studies. Our approach is to present trust studies in three main steps. Introducing trust theories as first attempts to grasp notions linked to the concept of trust, fields of application, that explicit the uses that are traditionally associated to computational trust, and finally trust models, as an instantiation of a trust theory, w.r.t. some formal framework. Our survey ends with a set of issues that we deem important to deal with in priority in order to help the advancement of the field. The next two chapters present two models of trust. Our first model is an instantiation of Castelfranchi & Falcone's socio-cognitive trust theory. Our model is implemented using a Dynamic Epistemic Logic that we propose. The main originality of our solution is the fact that our trust definition extends the original model to complex action (programs, composed services, etc.) and the use of authored assignment as a special kind of atomic actions. The use of our model is then illustrated in a case study related to service-oriented architecture. Our second model extends our socio-cognitive definition to an abductive framework that allows us to associate trust to explanations. Our framework is an adaptation of Bochman's production relations to the epistemic case. Since Bochman approach was initially proposed to study causality, our definition of trust in this second model presents trust as a special case of causal reasoning, applied to a social context. We end our manuscript with a conclusion that presents how we would like to extend our work.
Author: Sibel Adali
Publisher: Springer Science & Business Media
ISBN: 1461470315
Category : Computers
Languages : en
Pages : 90
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Book Description
We make complex decisions every day, requiring trust in many different entities for different reasons. These decisions are not made by combining many isolated trust evaluations. Many interlocking factors play a role, each dynamically impacting the others. In this brief, "trust context" is defined as the system level description of how the trust evaluation process unfolds. Networks today are part of almost all human activity, supporting and shaping it. Applications increasingly incorporate new interdependencies and new trust contexts. Social networks connect people and organizations throughout the globe in cooperative and competitive activities. Information is created and consumed at a global scale. Systems, devices, and sensors create and process data, manage physical systems, and participate in interactions with other entities, people and systems alike. To study trust in such applications, we need a multi-disciplinary approach. This book reviews the components of the trust context through a broad review of recent literature in many different fields of study. Common threads relevant to the trust context across many application domains are also illustrated. Illustrations in the text © 2013 Aaron Hertzmann. www.dgp.toronto.edu/~hertzman
Author: Brij B. Gupta
Publisher: CRC Press
ISBN: 0429995725
Category : Computers
Languages : en
Pages : 352
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Book Description
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.
Author: David C. Gibson
Publisher: Springer Nature
ISBN: 3031658981
Category :
Languages : en
Pages : 164
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Book Description
