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The 2021 International Conference on Machine Learning and Big Data Analytics for IoT Security and Privacy

SPIoT-2021 Volume 1

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.

that deposit competition will force banks to raise their own deposit interest rate, which will increase the cost and thus increase the ... Then we take the unbalanced data of 127 Chinese banks from 2011 to 2018 as the research samples.

Big Data and Artificial Intelligence in Digital Finance

Increasing Personalization and Trust in Digital Finance Using Big Data and AI

This open access book presents how cutting-edge digital technologies like Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector. The book illustrates how recent advances in these technologies facilitate banks, FinTechs, and financial institutions to collect, process, analyze, and fully leverage the very large amounts of data that are nowadays produced and exchanged in the sector. To this end, the book also introduces some of the most popular Big Data, AI and Blockchain applications in the sector, including novel applications in the areas of Know Your Customer (KYC), Personalized Wealth Management and Asset Management, Portfolio Risk Assessment, as well as variety of novel Usage-based Insurance applications based on Internet-of-Things data. Most of the presented applications have been developed, deployed and validated in real-life digital finance settings in the context of the European Commission funded INFINITECH project, which is a flagship innovation initiative for Big Data and AI in digital finance. This book is ideal for researchers and practitioners in Big Data, AI, banking and digital finance. Introduces the latest advances in Big Data and AI in Digital Finance that enable scalable, effective, and real-time analytics; Explains the merits of Blockchain technology in digital finance, including applications beyond the blockbuster cryptocurrencies; Presents practical applications of cutting edge digital technologies in the digital finance sector; Illustrates the regulatory environment of the financial sector and presents technical solutions that boost compliance to applicable regulations; This book is open access, which means that you have free and unlimited access.

This open access book presents how cutting-edge digital technologies like Machine Learning, Artificial Intelligence (AI), and Blockchain are set to disrupt the financial sector.

Application of Big Data, Blockchain, and Internet of Things for Education Informatization

Second EAI International Conference, BigIoT-EDU 2022, Virtual Event, July 29–31, 2022, Proceedings, Part I

The three-volume set LNICST 465, 466 and 467 constitutes the proceedings of the Second EAI International Conference on Application of Big Data, Blockchain, and Internet of Things for Education Informatization, BigIoT-EDU 2022, held as virtual event, in July 29–31, 2022. The 204 papers presented in the proceedings were carefully reviewed and selected from 550 submissions. BigIoT-EDU aims to provide international cooperation and exchange platform for big data and information education experts, scholars and enterprise developers to share research results, discuss existing problems and challenges, and explore cutting-edge science and technology. The conference focuses on research fields such as “Big Data” and “Information Education. The use of Artificial Intelligence (AI), Blockchain and network security lies at the heart of this conference as we focused on these emerging technologies to excel the progress of Big Data and information education.

Research on Channel Optimization Strategy Based on Data Mining Technology Dan Wang( B ) Sichuan University of Media ... After the combination of e-commerce and traditional banking, emerging self- service channels such as self-service ...

Big Data Analytics

5th International Conference, BDA 2017, Hyderabad, India, December 12-15, 2017, Proceedings

This book constitutes the refereed conference proceedings of the 5th International Conference on Big Data Analytics, BDA 2017, held in Hyderabad, India, in December 2017. The 21 revised full papers were carefully reviewed and selected from 80 submissions and cover topics on big data analytics, information and knowledge management, mining of massive datasets, computational modeling, data mining and analysis.

This aspect involves core banking, internet and mobile banking, e-wallets, m-wallets, Omni-channel data warehouse, Data Lake and service oriented architecture. Data. The data dimension deals with the quality of the data that is present ...

Advances in Big Data Analytics

Theory, Algorithms and Practices

Today, big data affects countless aspects of our daily lives. This book provides a comprehensive and cutting-edge study on big data analytics, based on the research findings and applications developed by the author and his colleagues in related areas. It addresses the concepts of big data analytics and/or data science, multi-criteria optimization for learning, expert and rule-based data analysis, support vector machines for classification, feature selection, data stream analysis, learning analysis, sentiment analysis, link analysis, and evaluation analysis. The book also explores lessons learned in applying big data to business, engineering and healthcare. Lastly, it addresses the advanced topic of intelligence-quotient (IQ) tests for artificial intelligence. /divSince each aspect mentioned above concerns a specific domain of application, taken together, the algorithms, procedures, analysis and empirical studies presented here offer a general picture of big data developments. Accordingly, the book can not only serve as a textbook for graduates with a fundamental grasp of training in big data analytics, but can also show practitioners how to use the proposed techniques to deal with real-world big data problems.

Portfolio models were derived from measurement of risk in portfolio of security, and extend to the measurement of systemic risk for a portfolio of banks [7]. The portfolio models follow two routines to measure a bank's systemic ...

Open and Big Data Management and Innovation

14th IFIP WG 6.11 Conference on e-Business, e-Services, and e-Society, I3E 2015, Delft, The Netherlands, October 13-15, 2015, Proceedings

This book constitutes the refereed conference proceedings of the 14th IFIP WG 6.11 Conference on e-Business, e-Services and e-Society, I3E 2015, held in Delft, The Netherlands, in October 2015. The 40 revised full papers presented together with 1 keynote panel were carefully reviewed and selected from 65 submissions. They are organized in the following topical sections: adoption; big and open data; e-business, e-services,, and e-society; and witness workshop.

income level as a considerable positive predictor of the customers' acceptance of Tele‐banking in Saudi Arabia. Likewise, according to Kolodinsky et al. [20], the adoption rate of Internet banking channels was observed to be in the ...

Fusing Big Data, Blockchain and Cryptocurrency

Their Individual and Combined Importance in the Digital Economy

As technology continues to revolutionise today’s economy, Big Data, Blockchain and Cryptocurrency are rapidly transforming themselves into mainstream functions within the financial services industry. This book examines each concept individually, analysing the opportunities and challenges they bring and exploring the potential for future development. The authors further evaluate the fusion of these three important products of the FinTech revolution, illustrating their combined influence on the digital economy. Providing a comprehensive analysis of three innovative technologies, this timely book will appeal to scholars researching innovation in the finance industry and financial services technology more specifically.

5.3.1 FinTech-Empowered Bank 4.0 and Financial Inclusion 5.3.1.1 Bank 4.0 If we now temporarily put the technical concepts and the advancements of more and more exciting technology-enabled financial solutions aside, in general, ...

Handbook of Big Data Privacy

This handbook provides comprehensive knowledge and includes an overview of the current state-of-the-art of Big Data Privacy, with chapters written by international world leaders from academia and industry working in this field. The first part of this book offers a review of security challenges in critical infrastructure and offers methods that utilize acritical intelligence (AI) techniques to overcome those issues. It then focuses on big data security and privacy issues in relation to developments in the Industry 4.0. Internet of Things (IoT) devices are becoming a major source of security and privacy concern in big data platforms. Multiple solutions that leverage machine learning for addressing security and privacy issues in IoT environments are also discussed this handbook. The second part of this handbook is focused on privacy and security issues in different layers of big data systems. It discusses about methods for evaluating security and privacy of big data systems on network, application and physical layers. This handbook elaborates on existing methods to use data analytic and AI techniques at different layers of big data platforms to identify privacy and security attacks. The final part of this handbook is focused on analyzing cyber threats applicable to the big data environments. It offers an in-depth review of attacks applicable to big data platforms in smart grids, smart farming, FinTech, and health sectors. Multiple solutions are presented to detect, prevent and analyze cyber-attacks and assess the impact of malicious payloads to those environments. This handbook provides information for security and privacy experts in most areas of big data including; FinTech, Industry 4.0, Internet of Things, Smart Grids, Smart Farming and more. Experts working in big data, privacy, security, forensics, malware analysis, machine learning and data analysts will find this handbook useful as a reference. Researchers and advanced-level computer science students focused on computer systems, Internet of Things, Smart Grid, Smart Farming, Industry 4.0 and network analysts will also find this handbook useful as a reference.

Bank User Should change password every 3 months. Use virtual keyboard to enter password rather than keyboard to Use trusted device and avoid using public network for e banking successfully login. enlisted on the banking website avoid ...

Technologies and Applications for Big Data Value

This open access book explores cutting-edge solutions and best practices for big data and data-driven AI applications for the data-driven economy. It provides the reader with a basis for understanding how technical issues can be overcome to offer real-world solutions to major industrial areas. The book starts with an introductory chapter that provides an overview of the book by positioning the following chapters in terms of their contributions to technology frameworks which are key elements of the Big Data Value Public-Private Partnership and the upcoming Partnership on AI, Data and Robotics. The remainder of the book is then arranged in two parts. The first part "Technologies and Methods" contains horizontal contributions of technologies and methods that enable data value chains to be applied in any sector. The second part "Processes and Applications" details experience reports and lessons from using big data and data-driven approaches in processes and applications. Its chapters are co-authored with industry experts and cover domains including health, law, finance, retail, manufacturing, mobility, and smart cities. Contributions emanate from the Big Data Value Public-Private Partnership and the Big Data Value Association, which have acted as the European data community's nucleus to bring together businesses with leading researchers to harness the value of data to benefit society, business, science, and industry. The book is of interest to two primary audiences, first, undergraduate and postgraduate students and researchers in various fields, including big data, data science, data engineering, and machine learning and AI. Second, practitioners and industry experts engaged in data-driven systems, software design and deployment projects who are interested in employing these advanced methods to address real-world problems.

using channels such as mobile apps or online banking, and they afterwards use this data for security and fraud-prevention processes. One of the processes is to identify relationships between customers and use them to verify posterior ...

Big Data in the GovTech System

This book presents applications and solutions of Big Data in the GovTech system and recommendations for regulating the institutions of the digital economy and information society for the wide application of Big Data with the use of the institutional approach. In this book, a systematic scientific understanding of GovTech is formed, the central place of Big Data in this system is substantiated, and modern experience in the functioning and development of this system is considered in detail. The contribution of the book to the literature is to bridge the gap between theory and practice of GovTech through a comprehensive study of all its manifestations in the three parts of the book. The first part is devoted to GovTech in the provision of high-tech educational services based on Big Data. The second part reflects state regulation of the economy by industry using Big Data in the GovTech. The third part outlined the digital divide and the experience of overcoming it with the help of GovTech based on Big Data. The practical significance of the book lies in the fact that it offers a holistic practical guide to the development of the GovTech system based on Big Data. The book will be of interest to academic scientists studying GovTech, as it clarified its categorical apparatus and scientific basis. The subjects of management in GovTech form the secondary target audience of this book, which provides them with numerous cases from the experience of modern Russia, as well as applied recommendations for improving the efficiency of the GovTech system based on Big Data. The book is multidisciplinary and is intended for scientists from various fields of science (pedagogy, economics, business, law, management, and ICT).

In July 2021, the Department of Statistics reflected in the report the cheapest banks in France in 2020 in terms of annual commissions for banking services in the area of Internet banking services [16]. Experience of Sweden In Sweden, ...