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Information
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Integrated Technologies-AI, IoT, Blockchain in Smart Cities Applications
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Integrated Technologies-AI, IoT, Blockchain in Smart Cities Applications

A special issue of Information (ISSN 2078-2489). This special issue belongs to the section "Information Processes".

Deadline for manuscript submissions: closed (30 April 2024) | Viewed by 18846

Special Issue Editors

Dr. Inam Ullah Khan

E-Mail Website
Guest Editor
Department of Engineering, King’s College London, London WC2R 2LS, UK
Interests: FANETs; UAVs; IoT; routing protocols; machine learning; graph theory
Dr. Mariya Ouaissa

E-Mail Website
Guest Editor
Laboratory of Modelisation of Mathematics and Computer Science, Moulay Ismail University, Meknes 50050, Morocco
Interests: AI; IoT; IoV; V2V; 5G; routing protocols
Dr. Tarandeep Kaur Bhatia

E-Mail Website
Guest Editor
School of Computer Science, University of Petroleum & Energy Studies (UPES), Uttarakhand 248007, India
Interests: WSN; routing protocols; UAVs; machine learning; cognitive IoT
Dr. Syed Bilal Hussain Shah

E-Mail Website
Guest Editor
School of Software, Dalian University of Technology, Dalian 116024, China
Interests: VANET; MANET; IoT; machine learning; data mining and cryptocurrency

Special Issue Information

Dear Colleagues,

This Special Issue will present extended versions of selected papers presented at the International Conference on Trends and Innovations in Smart Technologies (ICTIST 2022). The scope of ICTIST’22 is to provide a common platform for researchers, industry, academicians, engineers, scientists, and professionals all around the world. ICTIST’22 is organized to unite big minds under one roof and produce innovations that can revolutionize society. The conference covers all topics of communication networks, flying ad hoc networks, smart cities, Internet of things/Everything, blockchain, big data, computational intelligence, UAVs, artificial intelligence, ad hoc networks, SDN, underwater networks, machine learning, deep learning, image processing, and data analytics.

Dr. Inam Ullah Khan
Dr. Mariya Ouaissa
Dr. Tarandeep Kaur Bhatia
Dr. Syed Bilal Hussain Shah
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. Information 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 1600 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

  • UAVs
  • FANETs
  • Ad hoc networks
  • IoT
  • Machine learning
  • Deep learning
  • Smart cities

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Further information on MDPI's Special Issue polices can be found here.

Published Papers (5 papers)

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Research

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13 pages, 2072 KiB  
Article
Construction of a Human Resource Sharing System Based on Blockchain Technology
by Guoyao Zhu, Zhenyu Gu and Yonghui Dai
Information 2023, 14(3), 177; https://doi.org/10.3390/info14030177 - 11 Mar 2023
Cited by 1 | Viewed by 2256
Abstract
Human resource data sharing is very important for the cooperation of human resource institutions. Since the human resource data-sharing service needs to take into account the needs of individuals and talent service institutions, it faces issues such as the security of information sharing [...] Read more.
Human resource data sharing is very important for the cooperation of human resource institutions. Since the human resource data-sharing service needs to take into account the needs of individuals and talent service institutions, it faces issues such as the security of information sharing and the traceability of information. Therefore, this paper constructs a human resource data-sharing service system based on blockchain technology. Its trust mechanism is based on the Fabric alliance chain, and the system makes full use of its advantages of decentralization and consensus. Our research mainly includes data sharing architecture design, consensus mechanism analysis, smart contract design, data sharing process, and blockchain construction. The contribution of this paper is mainly in two aspects. On the one hand, it explores the trust mechanism of human resource data sharing and gives the scheme of the Fabric alliance chain. On the other hand, the overall architecture and smart contract design are given on the construction of the blockchain, which provides a reference for future research on human resource data sharing. Full article
(This article belongs to the Special Issue Integrated Technologies-AI, IoT, Blockchain in Smart Cities Applications)
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10 pages, 1459 KiB  
Article
Spyware Identification for Android Systems Using Fine Trees
by Muawya Naser and Qasem Abu Al-Haija
Information 2023, 14(2), 102; https://doi.org/10.3390/info14020102 - 7 Feb 2023
Cited by 5 | Viewed by 2653
Abstract
Android operating system (OS) has been recently featured as the most commonly used and ingratiated OS for smartphone ecosystems. This is due to its high interoperability as an open-source platform and its compatibility with all the major browsers within the mobile ecosystem. However, [...] Read more.
Android operating system (OS) has been recently featured as the most commonly used and ingratiated OS for smartphone ecosystems. This is due to its high interoperability as an open-source platform and its compatibility with all the major browsers within the mobile ecosystem. However, android is susceptible to a wide range of Spyware traffic that can endanger a mobile user in many ways, like password stealing and recording patterns of a user. This paper presents a spyware identification schemes for android systems making use of three different machine learning schemes, including fine decision trees (FDT), support vector machines (SVM), and the naïve Bayes classifier (NBC). The constructed models have been evaluated on a novel dataset (Spyware-Android 2022) using several performance measurement units such as accuracy, precision, and sensitivity. Our experimental simulation tests revealed the notability of the model-based FDT, making the peak accuracy 98.2%. The comparison with the state-of-art spyware identification models for android systems showed that our proposed model had improved the model’s accuracy by more than 18%. Full article
(This article belongs to the Special Issue Integrated Technologies-AI, IoT, Blockchain in Smart Cities Applications)
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20 pages, 5557 KiB  
Article
How the V4 Nations Handle the Idea of Smart Cities
by Roman Blazek, Pavol Durana and Jaroslav Jaros
Information 2022, 13(12), 570; https://doi.org/10.3390/info13120570 - 8 Dec 2022
Cited by 1 | Viewed by 2557
Abstract
Smart city is a term that includes digital, information, and communication technologies that contribute to increasing the level and quality of life in individual cities. It focuses primarily on the efficient use of existing resources but also on the discovery of new ones, [...] Read more.
Smart city is a term that includes digital, information, and communication technologies that contribute to increasing the level and quality of life in individual cities. It focuses primarily on the efficient use of existing resources but also on the discovery of new ones, with the goal of lowering energy consumption while also reducing environmental impact and optimizing traffic in specific areas of the city. This concept is increasingly coming to the fore. Thus, the aim of this article was to determine the level of involvement of Slovak, Czech, Polish, and Hungarian authors in solutions for Smart cities using Web of Science data. The analysis of countries that form the Visegrad Four (V4) region reveals how the region ranks compared to other countries that are actively involved in Smart cities based on VosViewer. To map a specific region of countries, it is necessary to first understand the underlying causes of the problem worldwide. Then, the status of the authors, the number of articles and citations, and universities may be actively discussed and graphically depicted for each nation in Visegrad. Based on the discovered results, academics can identify the contributors and institutions that have solved the issue individually or in co-authorships over a long period. The findings provide data for future testing of selected dependencies and a platform for creating a scientific model to rank countries. In addition, the authorities may focus on identified clusters of key areas that are an essential part of Smart cities and provide a higher quality of life in their city for the people. Full article
(This article belongs to the Special Issue Integrated Technologies-AI, IoT, Blockchain in Smart Cities Applications)
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23 pages, 1481 KiB  
Article
Enabling Blockchain with IoMT Devices for Healthcare
by Jameel Almalki, Waleed Al Shehri, Rashid Mehmood, Khalid Alsaif, Saeed M. Alshahrani, Najlaa Jannah and Nayyar Ahmed Khan
Information 2022, 13(10), 448; https://doi.org/10.3390/info13100448 - 25 Sep 2022
Cited by 24 | Viewed by 4452
Abstract
Significant modifications have been seen in healthcare facilities over the past two decades. With the use of IoT-enabled devices, the monitoring and analysis of patient diagnostic parameters is made considerably easy. The new technology shift for medical field is IoMT. However, the problem [...] Read more.
Significant modifications have been seen in healthcare facilities over the past two decades. With the use of IoT-enabled devices, the monitoring and analysis of patient diagnostic parameters is made considerably easy. The new technology shift for medical field is IoMT. However, the problem of privacy for patient data and the security of information still a point to ponder. This research proposed a prototype model to integrate the blockchain and IoMT for providing better analysis of patient health factors. The authors suggested IoMT data to be collected over Edge Computing gateway devices and forward to Cloud Gateway. The three-layered decision making structure ensures the integrity of the data. The further analysis of information collected over sensor-based devices is done in the Cloud IoT Central Hub service. To ensure the secrecy and compliance of the patient data, Smart Contracts are integrated. After the exchange of smart contracts, a block of information is broadcast over the health blockchain. The P2P network makes it viable to retain all health statistics and further processing of information. The paper describes the scenario and experimental setup for a COVID-19 data-set analyzed in the proposed prototype mode. After the collection of information and decision making, the block of data is sent across all peer nodes. Thus, the power of IoMT and blockchain makes it easy for the healthcare worker to diagnose and handle patient data with privacy. The IoMT is integrated with artificial intelligence to enable decision making based on the classification of data. The results are saved as transactions in the blockchain hyperledger. This study demonstrates the prototype model with test data in a testing network with two peer nodes. Full article
(This article belongs to the Special Issue Integrated Technologies-AI, IoT, Blockchain in Smart Cities Applications)
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Other

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21 pages, 4536 KiB  
Protocol
A Subjective Logical Framework-Based Trust Model for Wormhole Attack Detection and Mitigation in Low-Power and Lossy (RPL) IoT-Networks
by Sarmad Javed, Ahthasham Sajid, Tayybah Kiren, Inam Ullah Khan, Christine Dewi, Francesco Cauteruccio and Henoch Juli Christanto
Information 2023, 14(9), 478; https://doi.org/10.3390/info14090478 - 29 Aug 2023
Cited by 1 | Viewed by 2516
Abstract
The increasing use of wireless communication and IoT devices has raised concerns about security, particularly with regard to attacks on the Routing Protocol for Low-Power and Lossy Networks (RPL), such as the wormhole attack. In this study, the authors have used the trust [...] Read more.
The increasing use of wireless communication and IoT devices has raised concerns about security, particularly with regard to attacks on the Routing Protocol for Low-Power and Lossy Networks (RPL), such as the wormhole attack. In this study, the authors have used the trust concept called PCC-RPL (Parental Change Control RPL) over communicating nodes on IoT networks which prevents unsolicited parent changes by utilizing the trust concept. The aim of this study is to make the RPL protocol more secure by using a Subjective Logic Framework-based trust model to detect and mitigate a wormhole attack. The study evaluates the trust-based designed framework known as SLF-RPL (Subjective Logical Framework-Routing Protocol for Low-Power and Lossy Networks) over various key parameters, i.e., low energy consumption, packet loss ratio and attack detection rate. The achieved results were conducted using a Contiki OS-based Cooja Network simulator with 30, 60, and 90 nodes with respect to a 1:10 malicious node ratio and compared with the existing PCC-RPL protocol. The results show that the proposed SLF-RPL framework demonstrates higher efficiency (0.0504 J to 0.0728 J out of 1 J) than PCC-RPL (0.065 J to 0.0963 J out of 1 J) in terms of energy consumption at the node level, a decreased packet loss ratio of 16% at the node level, and an increased attack detection rate at network level from 0.42 to 0.55 in comparison with PCC-RPL. Full article
(This article belongs to the Special Issue Integrated Technologies-AI, IoT, Blockchain in Smart Cities Applications)
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