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Electronics
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Security and Privacy Protection in Cloud Computing: Trends and Challenges
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Security and Privacy Protection in Cloud Computing: Trends and Challenges

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

Deadline for manuscript submissions: closed (15 August 2025) | Viewed by 8951

Special Issue Editors

Dr. Mingyan Xiao

E-Mail Website
Guest Editor
Department of Computer Science, California State Polytechnic University, Pomona, CA 91768, USA
Interests: security and privacy in the general area of mobile computing and human-centered computing: security in crowdsourcing, data privacy; privacy in machine learning: differentially private learning algorithms
Dr. Huadi Zhu

E-Mail Website
Guest Editor
Department of Computer Science, Boise State University, Boise, ID 83725, USA
Interests: usable security on emerging cyber-physical systems; user-centered security and safety in everyday life applications; human-centered computing in real-world applications on novel platforms

Special Issue Information

Dear Colleagues,

The Special Issue on "Security and Privacy Protection in Cloud Computing: Trends and Challenges" aims to explore the evolving landscape of cybersecurity within cloud environments. As cloud computing continues to transform how businesses and individuals manage data and applications, ensuring robust security and privacy measures is paramount. This collection will delve into current trends and emerging challenges in securing cloud infrastructures, applications, and data, addressing issues such as data breaches, compliance with regulations like GDPR and CCPA, encryption techniques, identity and access management, and the role of artificial intelligence in enhancing security protocols. By synthesizing insights from both academia and industry, this Special Issue seeks to offer a comprehensive view of the state-of-the-art practices and research advancements in cloud security. The goal is to provide researchers, practitioners, and policymakers with valuable perspectives and strategies to mitigate risks and foster trust in cloud computing environments.

Dr. Mingyan Xiao
Dr. Huadi Zhu
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

  • cloud computing security
  • privacy protection
  • data breaches
  • encryption
  • identity and access management
  • regulatory compliance
  • artificial intelligence in cloud computing cybersecurity
  • threat detection
  • secure cloud architectures
  • risk mitigation

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Published Papers (2 papers)

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35 pages, 3122 KiB  
Article
Blockchain-Driven Smart Contracts for Advanced Authorization and Authentication in Cloud Security
by Mohammed Naif Alatawi
Electronics 2025, 14(15), 3104; https://doi.org/10.3390/electronics14153104 - 4 Aug 2025
Viewed by 501
Abstract
The increasing reliance on cloud services demands advanced security mechanisms to protect sensitive data and ensure robust access control. This study addresses critical challenges in cloud security by proposing a novel framework that integrates blockchain-based smart contracts to enhance authorization and authentication processes. [...] Read more.
The increasing reliance on cloud services demands advanced security mechanisms to protect sensitive data and ensure robust access control. This study addresses critical challenges in cloud security by proposing a novel framework that integrates blockchain-based smart contracts to enhance authorization and authentication processes. Smart contracts, as self-executing agreements embedded with predefined rules, enable decentralized, transparent, and tamper-proof mechanisms for managing access control in cloud environments. The proposed system mitigates prevalent threats such as unauthorized access, data breaches, and identity theft through an immutable and auditable security framework. A prototype system, developed using Ethereum blockchain and Solidity programming, demonstrates the feasibility and effectiveness of the approach. Rigorous evaluations reveal significant improvements in key metrics: security, with a 0% success rate for unauthorized access attempts; scalability, maintaining low response times for up to 100 concurrent users; and usability, with an average user satisfaction rating of 4.4 out of 5. These findings establish the efficacy of smart contract-based solutions in addressing critical vulnerabilities in cloud services while maintaining operational efficiency. The study underscores the transformative potential of blockchain and smart contracts in revolutionizing cloud security practices. Future research will focus on optimizing the system’s scalability for higher user loads and integrating advanced features such as adaptive authentication and anomaly detection for enhanced resilience across diverse cloud platforms. Full article
(This article belongs to the Special Issue Security and Privacy Protection in Cloud Computing: Trends and Challenges)
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Other

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60 pages, 1482 KiB  
Systematic Review
Federated Learning for Cloud and Edge Security: A Systematic Review of Challenges and AI Opportunities
by Latifa Albshaier, Seetah Almarri and Abdullah Albuali
Electronics 2025, 14(5), 1019; https://doi.org/10.3390/electronics14051019 - 3 Mar 2025
Cited by 10 | Viewed by 7924
Abstract
The ongoing evolution of cloud computing requires sustained attention to security, privacy, and compliance issues. The purpose of this paper is to systematically review the current literature regarding the application of federated learning (FL) and artificial intelligence (AI) to improve cloud computing security [...] Read more.
The ongoing evolution of cloud computing requires sustained attention to security, privacy, and compliance issues. The purpose of this paper is to systematically review the current literature regarding the application of federated learning (FL) and artificial intelligence (AI) to improve cloud computing security while preserving privacy, delivering real-time threat detection, and meeting regulatory requirements. The current research follows a systematic literature review (SLR) approach, which examined 30 studies published between 2020 and 2024 and followed the PRISMA 2020 checklist. The analysis shows that FL provides significant privacy risk reduction by 25%, especially in healthcare and similar domains, and it improves threat detection by 40% in critical infrastructure areas. A total of 80% of reviewed implementations showed improved privacy, but challenges like communication overhead and resource limitations persist, with 50% of studies reporting latency issues. To overcome these obstacles, this study also explores some emerging solutions, which include model compression, hybrid federated architectures, and cryptographic enhancements. Additionally, this paper demonstrates the unexploited capability of FL for real-time decision-making in dynamic edge environments and highlights its potential across autonomous systems, Industrial Internet of Things (IIoT), and cybersecurity frameworks. The paper’s proposed insights present a deployment strategy for FL models which enables scalable, secure, and privacy-preserving operations and will enable robust cloud security solutions in the AI era. Full article
(This article belongs to the Special Issue Security and Privacy Protection in Cloud Computing: Trends and Challenges)
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