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Smart Cities Research in Enabling Technologies and Tools
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Smart Cities Research in Enabling Technologies and Tools

A special issue of Journal of Risk and Financial Management (ISSN 1911-8074). This special issue belongs to the section "Financial Technology and Innovation".

Deadline for manuscript submissions: closed (31 December 2022) | Viewed by 12655

Special Issue Editors

Dr. Stephen Chan

E-Mail Website
Guest Editor
Department of Mathematics and Statistics, American University of Sharjah, Sharjah, United Arab Emirates
Interests: extreme value analysis and distribution theory in analysing financial commodities data and cryptocurrency data, and financial risk models
Special Issues, Collections and Topics in MDPI journals
Dr. Yuanyuan Zhang

E-Mail Website
Guest Editor
Center for Digital Trust and Society, Department of Criminology, University of Manchester, Manchester, UK
Interests: multivariate and extreme value analysis; big data sets; cryptocurrencies
Special Issues, Collections and Topics in MDPI journals
Dr. Shou Hsing Shih

E-Mail Website
Guest Editor
Department of Mathematics and Statistics, American University of Sharjah, Sharjah P.O. Box 26666, UAE
Interests: time series analysis; regression analysis; distribution theories; forecasting on environmental and economic applications
Dr. Jeffrey Chu

E-Mail Website
Guest Editor
School of Statistics, Renmin University of China, Beijing, China
Interests: statistics and distribution theory with financial applications; cryptocurrencies; blockchain and social networks
Special Issues, Collections and Topics in MDPI journals

Special Issue Information

Dear Colleagues,

Many countries around the world are beginning to move toward the idea of ‘smart cities’ through the development of more sustainable and efficient living environments. The aim of this Special Issue is to provide a collection of papers from leading experts that contribute to the development and enhancement of the supporting technologies required for smart city applications. The topics covered in this Special Issue include but are not limited to:

  • Blockchain and cryptocurrencies;
  • Internet of Things (IoT);
  • Data security;
  • Mobile broadband and 5G;
  • Big data and analytics;
  • Cloud computing;
  • Machine learning;
  • Logistics;
  • Business models,

Dr. Stephen Chan
Dr. Yuanyuan Zhang
Dr. Shou Hsing Shih
Dr. Jeffrey Chu
Guest Editors

Manuscript Submission Information

Manuscripts should be submitted online at www.mdpi.com by registering and logging in to this website. Once you are registered, click here to go to the submission form. Manuscripts can be submitted until the deadline. All submissions that pass pre-check are peer-reviewed. Accepted papers will be published continuously in the journal (as soon as accepted) and will be listed together on the special issue website. Research articles, review articles as well as short communications are invited. For planned papers, a title and short abstract (about 100 words) can be sent to the Editorial Office for announcement on this website.

Submitted manuscripts should not have been published previously, nor be under consideration for publication elsewhere (except conference proceedings papers). All manuscripts are thoroughly refereed through a single-blind peer-review process. A guide for authors and other relevant information for submission of manuscripts is available on the Instructions for Authors page. Journal of Risk and Financial Management is an international peer-reviewed open access monthly journal published by MDPI.

Please visit the Instructions for Authors page before submitting a manuscript. The Article Processing Charge (APC) for publication in this open access journal is 1400 CHF (Swiss Francs). Submitted papers should be well formatted and use good English. Authors may use MDPI's English editing service prior to publication or during author revisions.

Keywords

  • smart cities
  • blockchain and cryptocurrencies
  • Internet of Things (IoT)
  • mobile broadband and 5G
  • big data and analytics
  • machine learning
  • cloud computing

Published Papers (3 papers)

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Research

24 pages, 5872 KiB  
Article
Multiple Neighborhood Cellular Automata as a Mechanism for Creating an AGI on a Blockchain
by Konstantinos Sgantzos, Ian Grigg and Mohamed Al Hemairy
J. Risk Financial Manag. 2022, 15(8), 360; https://doi.org/10.3390/jrfm15080360 - 12 Aug 2022
Cited by 2 | Viewed by 7494
Abstract
Most Artificial Intelligence (AI) implementations so far are based on the exploration of how the human brain is designed. Nevertheless, while significant progress is shown on specialized tasks, creating an Artificial General Intelligence (AGI) remains elusive. This manuscript proposes that instead of asking [...] Read more.
Most Artificial Intelligence (AI) implementations so far are based on the exploration of how the human brain is designed. Nevertheless, while significant progress is shown on specialized tasks, creating an Artificial General Intelligence (AGI) remains elusive. This manuscript proposes that instead of asking how the brain is constructed, the main question should be how it was evolved. Since neurons can be understood as intelligent agents, intelligence can be thought of as a construct of multiple agents working and evolving together as a society, within a long-term memory and evolution context. More concretely, we suggest placing Multiple Neighborhood Cellular Automata (MNCA) on a blockchain with an interaction protocol and incentives to create an AGI. Given that such a model could become a “strong” AI, we present the conjecture that this infrastructure is possible to simulate the properties of cognition as an emergent phenomenon. Full article
(This article belongs to the Special Issue Smart Cities Research in Enabling Technologies and Tools)
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24 pages, 3160 KiB  
Article
HF-SCA: Hands-Free Strong Customer Authentication Based on a Memory-Guided Attention Mechanisms
by Cosimo Distante, Laura Fineo, Luca Mainetti, Luigi Manco, Benito Taccardi and Roberto Vergallo
J. Risk Financial Manag. 2022, 15(8), 342; https://doi.org/10.3390/jrfm15080342 - 03 Aug 2022
Cited by 4 | Viewed by 1781
Abstract
Strong customer authentication (SCA) is a requirement of the European Union Revised Directive on Payment Services (PSD2) which ensures that electronic payments are performed with multifactor authentication. While increasing the security of electronic payments, the SCA impacted seriously on the shopping carts abandonment: [...] Read more.
Strong customer authentication (SCA) is a requirement of the European Union Revised Directive on Payment Services (PSD2) which ensures that electronic payments are performed with multifactor authentication. While increasing the security of electronic payments, the SCA impacted seriously on the shopping carts abandonment: an Italian bank computed that 22% of online purchases in the first semester of 2021 did not complete because of problems with the SCA. Luckily, the PSD2 allows the use of transaction risk analysis tool to exempt the SCA process. In this paper, we propose an unsupervised novel combination of existing machine learning techniques able to determine if a purchase is typical or not for a specific customer, so that in the case of a typical purchase the SCA could be exempted. We modified a well-known architecture (U-net) by replacing convolutional blocks with squeeze-and-excitation blocks. After that, a memory network was added in a latent space and an attention mechanism was introduced in the decoding side of the network. The proposed solution was able to detect nontypical purchases by creating temporal correlations between transactions. The network achieved 97.7% of AUC score over a well-known dataset retrieved online. By using this approach, we found that 98% of purchases could be executed by securely exempting the SCA, while shortening the customer’s journey and providing an elevated user experience. As an additional validation, we developed an Alexa skill for Amazon smart glasses which allows a user to shop and pay online by merely using vocal interaction, leaving the hands free to perform other activities, for example driving a car. Full article
(This article belongs to the Special Issue Smart Cities Research in Enabling Technologies and Tools)
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45 pages, 669 KiB  
Article
Diffusion on the Peer-to-Peer Network
by Julien Riposo
J. Risk Financial Manag. 2022, 15(2), 47; https://doi.org/10.3390/jrfm15020047 - 20 Jan 2022
Cited by 2 | Viewed by 2809
Abstract
In a peer-to-peer complex environment, information is permanently diffused. Such an environment can be modeled as a graph, where there are flows of information. The interest of such modeling is that (1) one can describe the exchanges through time from an initial state [...] Read more.
In a peer-to-peer complex environment, information is permanently diffused. Such an environment can be modeled as a graph, where there are flows of information. The interest of such modeling is that (1) one can describe the exchanges through time from an initial state of the network, (2) the description can be used through the fit of a real-world case and to perform further forecasts, and (3) it can be used to trace information through time. In this paper, we review the methodology for describing diffusion processes on a network in the context of exchange of information in a crypto (Bitcoin) peer-to-peer network. Necessary definitions are posed, and the diffusion equation is derived by considering two different types of Laplacian operators. Equilibrium conditions are discussed, and analytical solutions are derived, particularly in the context of a directed graph, which constitutes the main innovation of this paper. Further innovations follow as the inclusion of boundary conditions, as well as the implementation of delay in the diffusion equation, followed by a discussion when doing approximations useful for the implementation. Numerous numerical simulations additionally illustrate the theory developed all along the paper. Specifically, we validated, through simple examples, the derived analytic solutions, and implemented them in more sophisticated graphs, e.g., the ring graph, particularly important in crypto peer-to-peer networks. As a conclusion for this article, we further developed a theory useful for fitting purposes in order to gain more information on its diffusivity, and through a modeling which the scientific community is aware of. Full article
(This article belongs to the Special Issue Smart Cities Research in Enabling Technologies and Tools)
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