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Author: Yuan Tian
Publisher: Springer Nature
ISBN: 9819933005
Category : Computers
Languages : en
Pages : 759
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Book Description
This book constitutes the refereed proceedings of the 4th International Conference on Big Data and Security, ICBDS 2022, held in Xiamen, China, during December 8–12, 2022. The 51 full papers and 3 short papers included in this book were carefully reviewed and selected from 211 submissions. They were organized in topical sections as follows: answer set programming; big data and new method; intelligence and machine learning security; data technology and network security; sybersecurity and privacy; IoT security.
Author: Yuan Tian
Publisher: Springer Nature
ISBN: 9819933005
Category : Computers
Languages : en
Pages : 759
Get Book Here
Book Description
This book constitutes the refereed proceedings of the 4th International Conference on Big Data and Security, ICBDS 2022, held in Xiamen, China, during December 8–12, 2022. The 51 full papers and 3 short papers included in this book were carefully reviewed and selected from 211 submissions. They were organized in topical sections as follows: answer set programming; big data and new method; intelligence and machine learning security; data technology and network security; sybersecurity and privacy; IoT security.
Author: Juan José Gude Prego
Publisher: Springer Nature
ISBN: 3030878724
Category : Technology & Engineering
Languages : en
Pages : 431
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Book Description
This book of Advances in Intelligent and Soft Computing contains accepted papers presented at CISIS 2021 and ICEUTE 2021, all conferences held in the beautiful and historic city of Bilbao (Spain), in September 2021. The aim of the 14th CISIS 20121 conference is to offer a meeting opportunity for academic and industry-related researchers belonging to the various, vast communities of computational intelligence, information security, and data mining. The need for intelligent, flexible behavior by large, complex systems, especially in mission-critical domains, is intended to be the catalyst and the aggregation stimulus for the overall event. After a through peer-review process, the CISIS 2021 International Program Committee selected 23 papers which are published in these conference proceedings achieving an acceptance rate of 40%. In this relevant edition, a special emphasis was put on the organization of special sessions. One special session is organized related to relevant topics as follows: building trust in ecosystems and ecosystem components. In the case of 12th ICEUTE 2021, the International Program Committee selected 17 papers, which are published in these conference proceedings. One special session is organized related to relevant topics as follows: sustainable personal goals: engaging students in their learning process. The selection of papers is extremely rigorous in order to maintain the high quality of the conference, and we would like to thank the members of the program committees for their hard work in the reviewing process. This is a crucial process to the creation of a high standard conference, and the CISIS and ICEUTE conferences would not exist without their help.
Author: Frank Hutter
Publisher: Springer Nature
ISBN: 3030676617
Category : Computers
Languages : en
Pages : 770
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Book Description
The 5-volume proceedings, LNAI 12457 until 12461 constitutes the refereed proceedings of the European Conference on Machine Learning and Knowledge Discovery in Databases, ECML PKDD 2020, which was held during September 14-18, 2020. The conference was planned to take place in Ghent, Belgium, but had to change to an online format due to the COVID-19 pandemic. The 232 full papers and 10 demo papers presented in this volume were carefully reviewed and selected for inclusion in the proceedings. The volumes are organized in topical sections as follows: Part I: Pattern Mining; clustering; privacy and fairness; (social) network analysis and computational social science; dimensionality reduction and autoencoders; domain adaptation; sketching, sampling, and binary projections; graphical models and causality; (spatio-) temporal data and recurrent neural networks; collaborative filtering and matrix completion. Part II: deep learning optimization and theory; active learning; adversarial learning; federated learning; Kernel methods and online learning; partial label learning; reinforcement learning; transfer and multi-task learning; Bayesian optimization and few-shot learning. Part III: Combinatorial optimization; large-scale optimization and differential privacy; boosting and ensemble methods; Bayesian methods; architecture of neural networks; graph neural networks; Gaussian processes; computer vision and image processing; natural language processing; bioinformatics. Part IV: applied data science: recommendation; applied data science: anomaly detection; applied data science: Web mining; applied data science: transportation; applied data science: activity recognition; applied data science: hardware and manufacturing; applied data science: spatiotemporal data. Part V: applied data science: social good; applied data science: healthcare; applied data science: e-commerce and finance; applied data science: computational social science; applied data science: sports; demo track.
Author: Amit Kumar Tyagi
Publisher: Springer Nature
ISBN: 9811976228
Category : Technology & Engineering
Languages : en
Pages : 407
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Book Description
This book provides fundamental principles of intelligent transport systems with comprehensive insight and state of the art of vehicles, vehicular technology, connecting vehicles, and intelligent vehicles/autonomous intelligent vehicles. The book discusses different approaches for multiple sensor-based multiple-objects tracking, in addition to blockchain-based solutions for building tamper-proof sensing devices. It introduces various algorithms for security, privacy, and trust for intelligent vehicles. This book countermeasures all the drawbacks and provides useful information to students, researchers, and scientific communities. It contains chapters from national and international experts and will be essential for researchers and advanced students from academia, and industry experts who are working on intelligent transportation systems.
Author: Dinesh C. Verma
Publisher: CRC Press
ISBN: 1000462528
Category : Computers
Languages : en
Pages : 218
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Book Description
This book provides an overview of Federated Learning and how it can be used to build real-world AI-enabled applications. Real-world AI applications frequently have training data distributed in many different locations, with data at different sites having different properties and different formats. In many cases, data movement is not permitted due to security concerns, bandwidth, cost or regulatory restriction. Under these conditions, techniques of federated learning can enable creation of practical applications. Creating practical applications requires implementation of the cycle of learning from data, inferring from data, and acting based on the inference. This book will be the first one to cover all stages of the Learn-Infer-Act cycle, and presents a set of patterns to apply federation to all stages. Another distinct feature of the book is the use of real-world applications with an approach that discusses all aspects that need to be considered in an operational system, including handling of data issues during federation, maintaining compliance with enterprise security policies, and simplifying the logistics of federated AI in enterprise contexts. The book considers federation from a manner agnostic to the actual AI models, allowing the concepts to be applied to all varieties of AI models. This book is probably the first one to cover the space of enterprise AI-based applications in a holistic manner.
Author: Zhao, Jingyuan
Publisher: IGI Global
ISBN: 1799896420
Category : Computers
Languages : en
Pages : 461
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Book Description
Necessity is the mother of invention; challenging times can provide new opportunities that must be detected and exploited at the right moments. The COVID-19 pandemic has demonstrated that it is not only an issue of healthcare but also a challenge for the global economy, business, and society. Organizations have rapidly deployed technology solutions that enable them to work and service remotely and continue most of their normal operations. The Handbook of Research on Technologies and Systems for E-Collaboration During Global Crises focuses on emerging technologies and systems, strategies, and solutions for e-collaboration. This book assesses the importance of technologies and systems for e-collaboration in dealing with emerging crises such as pandemics. Covering topics such as deep learning processes, machine vision, and profit-sharing models, it is an essential resource for computer scientists, public officials, engineers, students and professors of higher education, healthcare administration, programmers, researchers, and academicians.
Author: Aaisha Makkar
Publisher: Springer Nature
ISBN: 9811661863
Category : Computers
Languages : en
Pages : 186
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Book Description
This book addresses the issues with privacy and security in Internet of things (IoT) networks which are susceptible to cyber-attacks and proposes deep learning-based approaches using artificial neural networks models to achieve a safer and more secured IoT environment. Due to the inadequacy of existing solutions to cover the entire IoT network security spectrum, the book utilizes artificial neural network models, which are used to classify, recognize, and model complex data including images, voice, and text, to enhance the level of security and privacy of IoT. This is applied to several IoT applications which include wireless sensor networks (WSN), meter reading transmission in smart grid, vehicular ad hoc networks (VANET), industrial IoT and connected networks. The book serves as a reference for researchers, academics, and network engineers who want to develop enhanced security and privacy features in the design of IoT systems.
Author: Charles A. Kamhoua
Publisher: John Wiley & Sons
ISBN: 1119723922
Category : Technology & Engineering
Languages : en
Pages : 546
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Book Description
GAME THEORY AND MACHINE LEARNING FOR CYBER SECURITY Move beyond the foundations of machine learning and game theory in cyber security to the latest research in this cutting-edge field In Game Theory and Machine Learning for Cyber Security, a team of expert security researchers delivers a collection of central research contributions from both machine learning and game theory applicable to cybersecurity. The distinguished editors have included resources that address open research questions in game theory and machine learning applied to cyber security systems and examine the strengths and limitations of current game theoretic models for cyber security. Readers will explore the vulnerabilities of traditional machine learning algorithms and how they can be mitigated in an adversarial machine learning approach. The book offers a comprehensive suite of solutions to a broad range of technical issues in applying game theory and machine learning to solve cyber security challenges. Beginning with an introduction to foundational concepts in game theory, machine learning, cyber security, and cyber deception, the editors provide readers with resources that discuss the latest in hypergames, behavioral game theory, adversarial machine learning, generative adversarial networks, and multi-agent reinforcement learning. Readers will also enjoy: A thorough introduction to game theory for cyber deception, including scalable algorithms for identifying stealthy attackers in a game theoretic framework, honeypot allocation over attack graphs, and behavioral games for cyber deception An exploration of game theory for cyber security, including actionable game-theoretic adversarial intervention detection against advanced persistent threats Practical discussions of adversarial machine learning for cyber security, including adversarial machine learning in 5G security and machine learning-driven fault injection in cyber-physical systems In-depth examinations of generative models for cyber security Perfect for researchers, students, and experts in the fields of computer science and engineering, Game Theory and Machine Learning for Cyber Security is also an indispensable resource for industry professionals, military personnel, researchers, faculty, and students with an interest in cyber security.
Author: Yu-Chen Hu
Publisher: Springer Nature
ISBN: 9811679525
Category : Technology & Engineering
Languages : en
Pages : 620
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Book Description
This book features high-quality, peer-reviewed papers from the Fourth International Conference on Recent Advancements in Computer, Communication, and Computational Sciences (RACCCS 2021), held at Aryabhatta College of Engineering and Research Center, Ajmer, India, on August 20–21, 2021. Presenting the latest developments and technical solutions in computational sciences, it covers a variety of topics, such as intelligent hardware and software design, advanced communications, intelligent computing technologies, advanced software engineering, the web and informatics, and intelligent image processing. As such, it helps those in the computer industry and academia to use the advances in next-generation communication and computational technology to shape real-world applications.
Author: Archana Patel
Publisher: CRC Press
ISBN: 1000729184
Category : Computers
Languages : en
Pages : 405
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Book Description
Semantic web technologies (SWTs) offer the richest machine-interpretable (rather than just machine-processable) and explicit semantics that are being extensively used in various domains and industries. This book provides a roadmap for semantic web technologies (SWTs) and highlights their role in a wide range of domains including cloud computing, Internet of Things, big data, sensor network, and so forth. It also explores the prospects of these technologies including different data interchange formats, query languages, ontologies, Linked Data, and notations. The role of SWTs in ‘epidemic Covid-19’, ‘e-learning platforms and systems’, ‘block chain’, ‘open online courses’, and ‘visual analytics in healthcare’ is described as well. This book: Explores all the critical aspects of semantic web technologies (SWTs) Discusses the impact of SWTs on cloud computing, Internet of Things, big data, and sensor network Offers a comprehensive examination of the emerging research in the areas of SWTs and their related domains Provides a template to develop a wide range of smart and intelligent applications Includes latest applications and examples with real data This book is aimed at researchers and graduate students in computer science, informatics, web technology, cloud computing, and Internet of Things.
