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Electronics
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Data Security and Data Analytics in Cloud Computing
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Data Security and Data Analytics in Cloud Computing

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

Deadline for manuscript submissions: 15 November 2025 | Viewed by 9731

Special Issue Editors

Prof. Dr. Roberto Barchino

E-Mail Website
Guest Editor
Departamento de Ciencias de la Computación, Universidad de Alcalá, 28871 Madrid, Spain
Interests: virtualization technology; assessment; e-Learning; cloud computing; computer networks; tools learning and gamification
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. José Amelio Medina-Merodio

E-Mail Website
Guest Editor
Departamento de Ciencias de la Computación, Universidad de Alcalá, 28871 Madrid, Spain
Interests: virtualization technology; assessment; e-Learning; cloud computing; computer networks; tools learning and gamification
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. Salvador Otón Tortosa

E-Mail Website
Guest Editor
Department of Computer Science, Superior Polytechnic School, University of Alcalá, Edificio Politécnico, Campus Universitario Ctr Barcelona Km 33.6, 28871 Alcala de Henares, Spain
Interests: e-learning; learning technologies; accessibility; metadata; framewoks; Open Educational Resources (OER); interoperability
Special Issues, Collections and Topics in MDPI journals
Prof. Dr. José Javier Martínez-Herráiz

E-Mail Website
Guest Editor
Departamento de Ciencias de la Computación, Universidad de Alcalá, 28871 Madrid, Spain
Interests: cybersecurity; artificial intelligence; mobile technologies; gamification; learning technology

Special Issue Information

Dear Colleagues, 

The digital revolution has catapulted cloud computing to the forefront of technological transformation, offering a flexible and scalable paradigm that redefines the way we conceive and manage computing. This Special Issue aims to delve into the various dimensions of cloud computing, highlighting current challenges, emerging innovations, and future horizons in this dynamic field.

We invite researchers, academics, and professionals to contribute their original research, theoretical approaches, and case studies addressing key issues in the realm of cloud computing. Topics of interest include, but are not limited to:

  • Cloud applications and architectures;
  • Public, private, and hybrid clouds;
  • Industry 4.0;
  • Data security;
  • Security and privacy;
  • Digital transformation;
  • Artificial intelligence;
  • Virtual and augmented reality;
  • Internet of Things;  
  • Data analytics;
  • Data mining;
  • Machine learning;
  • Cyber security;   
  • Digital twins;
  • Health care;
  • Ethical challenges in the era of cloud computing.

This Special Issue will provide a platform for discussion and the exchange of innovative ideas, fostering collaboration among experts and industry leaders. Join us in exploring the frontiers of cloud computing and contributing to the ongoing advancement of this exciting discipline.

Prof. Dr. Roberto Barchino
Prof. Dr. José Amelio Medina-Merodio
Prof. Dr. Salvador Otón Tortosa
Prof. Dr. José Javier Martínez-Herráiz
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

  • data security
  • data analytics
  • cloud computing

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

Published Papers (3 papers)

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Research

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31 pages, 7959 KiB  
Article
Introducing Security Mechanisms in OpenFog-Compliant Smart Buildings
by Imanol Martín Toral, Isidro Calvo, Eneko Villar, Jose Miguel Gil-García and Oscar Barambones
Electronics 2024, 13(15), 2900; https://doi.org/10.3390/electronics13152900 - 23 Jul 2024
Cited by 2 | Viewed by 1274
Abstract
Designing smart building IoT applications is a complex task. It requires efficiently integrating a broad number of heterogeneous, low-resource devices that adopt lightweight strategies. IoT frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 [...] Read more.
Designing smart building IoT applications is a complex task. It requires efficiently integrating a broad number of heterogeneous, low-resource devices that adopt lightweight strategies. IoT frameworks, especially if they are standard-based, may help designers to scaffold the applications. OpenFog, established as IEEE 1934 standard, promotes the use of free open source (FOS) technologies and has been identified for use in smart buildings. However, smart building systems may present vulnerabilities, which can put their integrity at risk. Adopting state-of-the-art security mechanisms in this domain is critical but not trivial. It complicates the design and operation of the applications, increasing the cost of the deployed systems. In addition, difficulties may arise in finding qualified cybersecurity personnel. OpenFog identifies the security requirements of the applications, although it does not describe clearly how to implement them. This article presents a scalable architecture, based on the OpenFog reference architecture, to provide security by design in buildings of different sizes. It adopts FOS technologies over low-cost IoT devices. Moreover, it presents guidelines to help developers create secure applications, even if they are not security experts. It also proposes a selection of technologies in different layers to achieve the security dimensions defined in the X.805 ITU-T recommendation. A proof-of-concept Indoor Environment Quality (IEQ) system, based on low-cost smart nodes, was deployed in the Faculty of Engineering of Vitoria-Gasteiz to illustrate the implementation of the presented approach. The operation of the IEQ system was analyzed using software tools frequently used to find vulnerabilities in IoT applications. The use of state-of-the-art security mechanisms such as encryption, certificates, protocol selection and network partitioning/configuration in the OpenFog-based architecture improves smart building security. Full article
(This article belongs to the Special Issue Data Security and Data Analytics in Cloud Computing)
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28 pages, 8341 KiB  
Article
Intelligent Threat Detection—AI-Driven Analysis of Honeypot Data to Counter Cyber Threats
by Phani Lanka, Khushi Gupta and Cihan Varol
Electronics 2024, 13(13), 2465; https://doi.org/10.3390/electronics13132465 - 24 Jun 2024
Cited by 6 | Viewed by 6710
Abstract
Security adversaries are rampant on the Internet, constantly seeking vulnerabilities to exploit. The sheer proliferation of these sophisticated threats necessitates innovative and swift defensive measures to protect the vulnerable infrastructure. Tools such as honeypots effectively determine adversary behavior and safeguard critical organizational systems. [...] Read more.
Security adversaries are rampant on the Internet, constantly seeking vulnerabilities to exploit. The sheer proliferation of these sophisticated threats necessitates innovative and swift defensive measures to protect the vulnerable infrastructure. Tools such as honeypots effectively determine adversary behavior and safeguard critical organizational systems. However, it takes a significant amount of time to analyze these attacks on the honeypots, and by the time actionable intelligence is gathered from the attacker’s tactics, techniques, and procedures (TTPs), it is often too late to prevent potential damage to the organization’s critical systems. This paper contributes to the advancement of cybersecurity practices by presenting a cutting-edge methodology, capitalizing on the synergy between artificial intelligence and threat analysis to combat evolving cyber threats. The current research articulates a novel strategy, outlining a method to analyze large volumes of attacker data from honeypots utilizing large language models (LLMs) to assimilate TTPs and apply this knowledge to identify real-time anomalies in regular user activity. The effectiveness of this model is tested in real-world scenarios, demonstrating a notable reduction in response time for detecting malicious activities in critical infrastructure. Moreover, we delve into the proposed framework’s practical implementation considerations and scalability, underscoring its adaptability in diverse organizational contexts. Full article
(This article belongs to the Special Issue Data Security and Data Analytics in Cloud Computing)
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Review

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19 pages, 1210 KiB  
Review
A Narrative Review of Identity, Data and Location Privacy Techniques in Edge Computing and Mobile Crowdsourcing
by Syed Raza Bashir, Shaina Raza and Vojislav Misic
Electronics 2024, 13(21), 4228; https://doi.org/10.3390/electronics13214228 - 28 Oct 2024
Cited by 1 | Viewed by 1146
Abstract
As digital technology advances, the proliferation of connected devices poses significant challenges and opportunities in mobile crowdsourcing and edge computing. This narrative review focuses on the need for privacy protection in these fields, emphasizing the increasing importance of data security in a data-driven [...] Read more.
As digital technology advances, the proliferation of connected devices poses significant challenges and opportunities in mobile crowdsourcing and edge computing. This narrative review focuses on the need for privacy protection in these fields, emphasizing the increasing importance of data security in a data-driven world. Through an analysis of contemporary academic literature, this review provides an understanding of the current trends and privacy concerns in mobile crowdsourcing and edge computing. We present insights and highlight advancements in privacy-preserving techniques, addressing identity, data, and location privacy. This review also discusses the potential directions that can be useful resources for researchers, industry professionals, and policymakers. Full article
(This article belongs to the Special Issue Data Security and Data Analytics in Cloud Computing)
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