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E-book

Title Big data privacy and security in smart cities Richard Jiang, Ahmed Bouridane, Chang-Tsun Li, Danny Crookes, Said Boussakta, Feng Hao, Eran A. Edirisinghe, editors
Published Cham : Springer, 2022

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Description 1 online resource
Series Advanced sciences and technologies for security applications
Advanced sciences and technologies for security applications.
Contents 1. Introduction -- 2. Deep Digital Identity for Big Data Privacy and Security -- 3. Behavioral Biometrics for Security in Smart Cities -- 4. Identity Spoofing and Cyber Attacks -- 5. Intrusion Detection via Deep Learning -- 6. Biometric Blockchain in e-Governance -- 7. e-Voting and Transparent Democracy -- 8. Secured e-Trading with Blockchain -- 9. Healthcare Biometric Blockchain -- 10. Medical Data and Security -- 11. Digital Passport -- 12. Social Smart Cities -- 13. Forensics and Legislation -- 14. Soft Border Control with Digital IDs
Summary This book highlights recent advances in smart cities technologies, with a focus on new technologies such as biometrics, blockchains, data encryption, data mining, machine learning, deep learning, cloud security, and mobile security. During the past five years, digital cities have been emerging as a technology reality that will come to dominate the usual life of people, in either developed or developing countries. Particularly, with big data issues from smart cities, privacy and security have been a widely concerned matter due to its relevance and sensitivity extensively present in cybersecurity, healthcare, medical service, e-commercial, e-governance, mobile banking, e-finance, digital twins, and so on. These new topics rises up with the era of smart cities and mostly associate with public sectors, which are vital to the modern life of people. This volume summarizes the recent advances in addressing the challenges on big data privacy and security in smart cities and points out the future research direction around this new challenging topic
Bibliography References -- Predictive Maintenance of Vehicle Fleets Using LSTM Autoencoders for Industrial IoT Datasets -- 1 Introduction -- 2 Related Work -- 3 Computational Method -- 3.1 Datasets -- 3.2 LSTM Autoencoder for Predictive Maintenance -- 4 Experiments and Results -- 5 Conclusion -- References -- A Comparative Study on the User Experience on Using Secure Messaging Tools -- 1 Introduction -- 2 Literature Review -- 2.1 User Experience Research -- 2.2 Obstacles to the Adoption of Secure Communication Tools -- 2.3 Previous Email Encryption Studies -- 3 Problem Statement -- 4 Research Methodology
Notes Print version record
Subject Data privacy.
Big data -- Security measures
Smart cities -- Security measures
Cities and towns -- Technological innovations
Data privacy
Genre/Form Electronic books
Form Electronic book
Author Jiang, Richard, editor
Bouridane, Ahmed, editor
Li, Chang-Tsun, editor
Crookes, Danny, editor
Boussakta, Said, editor
Hao, Feng, editor
Edirisinghe, Eran A. editor
ISBN 9783031044243
303104424X