Big Data Privacy and Security in Smart Cities (eng)
Idioma: inglés
Editorial: Springer, 2022
Serie: Libro 80 de 100 - Advanced Sciences and Technologies for Security Applications
- Tapa dura
- Nuevo

Librería: Brook Bookstore On Demand, Napoli, NA, ItaliaBrook Bookstore On Demand
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N° de ref. del artículo GLVJFFGOJR
- Título
- Big Data Privacy and Security in Smart Cities (eng)
- Autor
- Bouridane, Ahmed
- Editorial
- Springer
- Año de publicación
- 2022
- Estado
- new
- Encuadernación
- Encuadernación de tapa dura
- Idioma
- inglés
- ISBN 10
- 3031044231
- ISBN 13
- 9783031044236
- Peso del artículo
- 0,54 kilogramos
- Serie
- Libro 80 de 100: Advanced Sciences and Technologies for Security Applications
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.
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Acerca del autor
Said Boussakta is Professor of Communications and Signal Processing at the ISC Group in the School of Engineering at Newcastle University. He has over 27 year research experience in digital signal processing and communications. His major research contributions are in the areas of fast transforms and algorithms for communication and signal processing applications, encryption techniques, and bio-inspired technologies 1. He has received funding EPSRC (GR/M42060/01, GR/S98160/01, GR/S08160/02, EP/H004637), MOD (2043/097), EU (Co-Health) and industry (e.g. Schlumberger and BTL Medical). He has published over 200 articles and is currently supervising a large number of research projects. More recently he has led work on encryption, communications, and e-Health. He is a member of EPSRC Peer Review College, the chair, and technical committee member of international conferences, e.g. ICC, Senior Member of IEEE and Fellow of the IET. Prof. S. Boussakta has over 16 years research experience in digital signal and image processing, fast transforms and algorithms, DSP and communications, including six years as Senior Research Associate. His major research interests are in the areas of fast transforms and algorithms for DSP and multidimensional signal processing applications, encryption techniques, digital signal processing and communications techniques and systems. He has successfully introduced and developed many new algorithms and transforms [1-8]. His research experience has been through projects supported by industry (Schlumberger, BTL Medical, HW Communications etc..), EPSRC GR/M42060/01 and GR/M42060/02 ‘A Novel Hybrid Parallel Method for Digital Image and Multidimensional Signal Processing Applications’, EPSRC GR/S98160/01 and GR/S08160/02 ‘New Approach to Data Encryption Using Two-dimensional New Transforms’, MOD (DRA Agreement No. 2043/097) ‘Finite Number Systems in Digital Signal Processing’ and the Royal Society (Q803) Spreading Sequences Design for Future CDMA Communications Systems. He has published over 100 papers in international journals and conference proceedings and is currently supervising a number of research projects. Prof. Boussakta has an international reputation in his field. More recently he has led work on the development of multidimensional algorithms for 3D applications [2, 7]. He is a member of EPSRC Peer Review College, the chair of the Signal Processing for Communications Symposium at ICC06, ICC07, and ICC08, a member of the technical committees of several international conferences, a senior member of IEEE Communications, member of the Signal Processing and Computer Societies and a fellow of the IET.
Professor Feng Hao is a professor of Security Engineering at the Department of Computer Science, University of Warwick. He graduated with a PhD from the Security Group, at the Computer Laboratory, University of Cambridge. I had six years working experience in security industry with a CISSP before joining Newcastle University Computing Science as a lecturer in December 2010. His research interest (and that of my research team) is primarily driven by tackling real-world security problems. He proposed the first secure solution to combine iris biometrics and cryptography, the two complementary security technologies. His paper ‘Combining crypto with biometrics effectively’ (IEEE Trans. on Computers, 2006) is ranked the top among the Google Scholar Classic Papers in the category of computer security and cryptography. With colleagues, he designed a few cryptographic protocols: AV-net (so far the most efficient solution to the Dining Cryptographers problem), YAK, J-PAKE, Open Vote network, DRE-i and DRE-ip (demo). So far, none of these protocols have been broken. Besides designing secure protocols, he cryptanalyzes insecure protocols. With Siamak Shahandashti, he found and fixed security weaknesses in SPEKE, a password-authenticated key exchange protocol that has been standardized in IEEE P1363.2 and ISO/IEC 11770-4. The attacks have been acknowledged by ISO/IEC SC 27 Work Group 2, and the standard has been revised in 2017 to incorporate their proposed fix. His research has been supported by many grants such as the 1.5 million euros ERC starting grant to support his further investigation on SEEV (one of the 7 such awards in computer science in the UK, and 34 in total in the Europe), and in 2015, a follow-up ERC Proof of Concept grant to support commercialization of SEEV.
Professor Eran A. Edirisinghe is currently the Pro Vice-Chancellor (Research & Innovation) of Keele University. He joined Keele University in August 2021, having previously served at Loughborough University in various academic and leadership roles, including being the Head of Department of Computer Science (2011-2014) and Associate Dean for Enterprise, School of Science (2015-2021). Having received a BSc.Eng.(Hons.) degree in Electronic & Telecommunication Engineering from Moratuwa University, Sri Lanka, in 1994, Eran received his MSc degree in Digital Communication Systems and PhD degree in Computer Science from Loughborough University, in 1996 and 1999, respectively. He joined Loughborough University as a Lecturer in Computer Science in 2000. His research expertise is in the areas of image processing, image enhancement, video coding, computer vision, pattern recognition, machine learning and deep neural networks. Eran’s research has contributed significantly to the UK industry and economy. He actively contributed to the strengthening of the R&I portfolio of Apical Ltd., a global award-winning UK based SME that supplied smart digital camera and display technology to all top mobile, digital camera and TV brands, which was acquired by ARM UK in 2016 for a record $320M. His research group’s partnership with Apical Ltd., was awarded the prestigious, Loughborough University Enterprise Award for Knowledge Transfer in both 2013 and 2014. Eran has held research grants to the value of over £15M funded by the EPSRC, DTI/Innovate UK, UK industry and has collaborated with 30+ industry partners in delivering high impact research. He has also published 180+ academic papers and 20+ confidential industry research reports. A passionate advocate of PhD student supervision and training, Eran has supervised over 40 PhD students, many of whom hold senior leadership positions in UK/International universities and industry. He continues to focus on conducting high impact, applied research in Deep Neural Networks supported, imaging applications in digital cameras, drones, automated document analysis systems, future smart-TVs and display systems.
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