Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
4.7
2.9
Journals
Electronics
Special Issues
Cyber-Security in Smart Cities: Challenges and Solution
share announcement

Cyber-Security in Smart Cities: Challenges and Solution

A special issue of Electronics (ISSN 2079-9292). This special issue belongs to the section "Computer Science & Engineering".

Deadline for manuscript submissions: 15 June 2024 | Viewed by 7767

Special Issue Editors

Dr. Muath Obaidat

E-Mail Website
Guest Editor
Computer Science Department, City University of New York, New York, NY 10019, USA
Interests: wireless and mobile security; network security and forensics; IoT security and privacy; cybersecurity and machine learning
Special Issues, Collections and Topics in MDPI journals
Dr. Kutub Thakur

E-Mail Website
Guest Editor
Department of Professional Security Studies, New Jersey City University, Jersey City, NJ 07305, USA
Interests: digital forensics; network security; machine learning; IoT security; privacy; user behavior

Special Issue Information

Dear Colleagues,

Technological advancements, including smart cities and their building blocks (e.g., WSNs and IoT-connected devices) have created an internet of vulnerabilities (IoV) which is put at risk by an alarming rise in adversarial cyber-attacks targeting a wide range of systems and applications. It is apparent that more novelty will be critical to enhance the current state of cybersecurity across multiple domains, technologies and industries, particularly smart cities, WSNs and the IoT ecosystem to ensure the resilience and trust in our systems.

To that end, this Special Issue titled “Cyber-Security in Smart Cities: Challenges and Solution” invites scholars proposing new original research and developments in the domain of security and privacy that pertain to the domains of wireless sensor networks (WSNs), IoT ecosystem, smart cities, networks, and communications. We particularly encourage submissions with high-quality research and scholarly works proposing theoretical, practical, innovative and scalable approaches to cyber-security and privacy in its broad definition, as well as comprehensive literature reviews and surveys.

This Special Issue on “Cyber-Security in Smart Cities: Challenges and Solution” solicits articles in multiple domains and topics including but not limited to those listed in the provided keywords:

  • Cyber-security frameworks
  • Internet of things for smart cities applications
  • Wireless and mobile networks security
  • Data security techniques related to smart cities
  • Critical infrastructures security
  • Privacy and anonymity solutions for smart cities
  • Secure smart cities devices communication
  • IoT and mobile devices security
  • Privacy and security issues for smart cities applications
  • Digital forensics
  • Cyber-threats against all digital systems and devices
  • Cloud, fog and edge computing security
  • Trust/blockchain for systems security
  • AI and machine learning for security
  • Effects of cyber-security on smart cities

Dr. Muath Obaidat
Dr. Kutub Thakur
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. Electronics is an international peer-reviewed open access semimonthly 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 2400 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

  • cyber-security frameworks
  • internet of things for smart cities applications
  • wireless and mobile networks security
  • data security techniques related to smart cities
  • critical infrastructures security
  • privacy and anonymity solutions for smart cities
  • secure smart cities devices communication
  • IoT and mobile devices security
  • privacy and security issues for smart cities applications
  • digital forensics
  • cyber-threats against all digital systems and devices
  • cloud, fog and edge computing security
  • trust/blockchain for systems security
  • AI and machine learning for security
  • effects of cyber-security on smart cities

Published Papers (3 papers)

Download All Papers
Order results
Result details
Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:

Research

Jump to: Other

28 pages, 5023 KiB  
Article
Lightweight and Secure Multi-Message Multi-Receiver Certificateless Signcryption Scheme for the Internet of Vehicles
by Guishuang Xu, Xinchun Yin and Xincheng Li
Electronics 2023, 12(24), 4908; https://doi.org/10.3390/electronics12244908 - 06 Dec 2023
Cited by 1 | Viewed by 685
Abstract
The Internet of Vehicles (IoV) improves traffic efficiency and enhances driving safety through the real-time collection and analysis of traffic-related data. Numerous secure and privacy-preserving communication protocols have been proposed for the IoV. However, various security threats, privacy leakage, and inefficient communications remain [...] Read more.
The Internet of Vehicles (IoV) improves traffic efficiency and enhances driving safety through the real-time collection and analysis of traffic-related data. Numerous secure and privacy-preserving communication protocols have been proposed for the IoV. However, various security threats, privacy leakage, and inefficient communications remain unaddressed. Therefore, a lightweight and secure multi-message multi-receiver certificateless signcryption (LS-MRCLSC) scheme based on elliptic curve cryptography (ECC) is proposed. The proposed scheme guarantees secure communication and promotes messaging efficiency with multi-cast mode. Multiple key generation centers (KGCs) collaborate to generate and update the system master key (SMK) using Feldman’s verifiable secret-sharing (FVSS) algorithm, avoiding the single point of failure (SPoF) problem. Formal security proofs under the random oracle model (ROM) demonstrate that the proposed scheme meets requirements such as data confidentiality, message unforgeability, anonymity, and unlinkability. Performance evaluations confirm that the LS-MRCLSC scheme is better than similar schemes in terms of efficiency, feasibility, and scalability. Full article
(This article belongs to the Special Issue Cyber-Security in Smart Cities: Challenges and Solution)
►▼ Show Figures

Figure 1

18 pages, 1053 KiB  
Article
Distributed K-Anonymous Location Privacy Protection Algorithm Based on Interest Points and User Social Behavior
by Ling Xing, Dexin Zhang, Honghai Wu, Huahong Ma and Xiaohui Zhang
Electronics 2023, 12(11), 2446; https://doi.org/10.3390/electronics12112446 - 29 May 2023
Cited by 1 | Viewed by 1213
Abstract
Location-based services have become an important part of our daily lives, and while users enjoy convenient Internet services, they also face the risk of privacy leakage. K-anonymity is a widely used method to protect location privacy, but most existing K-anonymity location privacy protection [...] Read more.
Location-based services have become an important part of our daily lives, and while users enjoy convenient Internet services, they also face the risk of privacy leakage. K-anonymity is a widely used method to protect location privacy, but most existing K-anonymity location privacy protection schemes use virtual locations to construct anonymity zones, which have the problem of being vulnerable to attackers through background knowledge, while the improved collaborative K-anonymity scheme does not sufficiently consider whether collaborating users share similar attributes. We propose a distributed K-anonymity location privacy-preserving algorithm based on interest points and user social behaviors to solve these problems in existing K-anonymity schemes. The method determines the similarity of users by their interest points and social behaviors and then selects users with high similarity to build an anonymous set of collaborative users. Finally, to ensure the relatively uniform distribution of collaborative users, a homogenization algorithm is used to make the anonymous location points as dispersed as possible. The experimental results showed that our algorithm can effectively resist background attacks, and the uniformly distributed anonymous location points can achieve higher-quality anonymous regions. Full article
(This article belongs to the Special Issue Cyber-Security in Smart Cities: Challenges and Solution)
►▼ Show Figures

Figure 1

Other

Jump to: Research

26 pages, 1568 KiB  
Systematic Review
A Systematic Review on Deep-Learning-Based Phishing Email Detection
by Kutub Thakur, Md Liakat Ali, Muath A. Obaidat and Abu Kamruzzaman
Electronics 2023, 12(21), 4545; https://doi.org/10.3390/electronics12214545 - 05 Nov 2023
Cited by 2 | Viewed by 4903
Abstract
Phishing attacks are a growing concern for individuals and organizations alike, with the potential to cause significant financial and reputational damage. Traditional methods for detecting phishing attacks, such as blacklists and signature-based techniques, have limitations that have led to developing more advanced techniques. [...] Read more.
Phishing attacks are a growing concern for individuals and organizations alike, with the potential to cause significant financial and reputational damage. Traditional methods for detecting phishing attacks, such as blacklists and signature-based techniques, have limitations that have led to developing more advanced techniques. In recent years, machine learning and deep learning techniques have gained attention for their potential to improve the accuracy of phishing detection. Deep learning algorithms, such as CNNs and LSTMs, are designed to learn from patterns and identify anomalies in data, making them more effective in detecting sophisticated phishing attempts. To develop a comprehensive understanding of the current state of research on the use of deep learning techniques for phishing detection, a systematic literature review is necessary. This review aims to identify the various deep learning techniques used for phishing detection, their effectiveness, and areas for future research. By synthesizing the findings of relevant studies, this review identifies the strengths and limitations of different approaches and provides insights into the challenges that need to be addressed to improve the accuracy and effectiveness of phishing detection. This review aims to contribute to developing a coherent and evidence-based understanding of the use of deep learning techniques for phishing detection. The review identifies gaps in the literature and informs the development of future research questions and areas of focus. With the increasing sophistication of phishing attacks, applying deep learning in this area is a critical and rapidly evolving field. This systematic literature review aims to provide insights into the current state of research and identify areas for future research to advance the field of phishing detection using deep learning. Full article
(This article belongs to the Special Issue Cyber-Security in Smart Cities: Challenges and Solution)
►▼ Show Figures

Figure 1

Show export options expand_more Show export options expand_less
Select all
Export citation of selected articles as:
 
Displaying articles 1-3
Back to TopTop