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Secure Cloud Computing Infrastructures

A special issue of Applied Sciences (ISSN 2076-3417). This special issue belongs to the section "Computing and Artificial Intelligence".

Deadline for manuscript submissions: closed (20 January 2026) | Viewed by 5450

Special Issue Editor


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Guest Editor
Department of Computers and Systems, Federal University of Campina Grande, Campina Grande 58190-970, Brazil
Interests: cloud computing; cybersecurity; confidential computing

Special Issue Information

Dear Colleagues,

As concerns regarding cybersecurity increase, so does the need to collect evidence of security and privacy guarantees. This demand has fostered research on various approaches and technologies for implementing trustworthy infrastructure. Nevertheless, in cloud computing environments, where a provider manages a complex stack of software that reduces costs and eases operation for its tenants, this is a significant challenge. Vulnerabilities in the underlying infrastructure can compromise even carefully implemented applications. This Special Issue aims to share results and novel ideas on designing, evaluating, and applying techniques that enable secure cloud computing infrastructures.

An example of a related topic is the advent of trusted execution environments (TEEs). TEEs enable confidential computing and can potentially take security in cloud computing to the next level, isolating the user workloads from a compromised host. Still, there are many challenges in hardware and software for confidential computing. For example, deploying an application in a confidential VM does not comply with the confidential computing threat model (e.g., the application may naively use storage services controlled by the cloud provider). Therefore, the challenges in secure cloud infrastructure extend to other areas of secure infrastructure, including limitations, usability, new threats, performance and cost impacts, interoperability, supply chain security, and so on.

This Special Issue welcomes original research papers in the following intersecting fields:

  • Cloud, edge, and fog computing;
  • Parallel and distributed computing;
  • Hardware architectures;
  • Privacy-preserving artificial intelligence and machine learning;
  • Verification and validation.

Prof. Dr. Andrey Brito
Guest Editor

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Keywords

  • trusted platforms and trustworthy infrastructures
  • confidential computing and its limitations
  • trusted execution environments
  • attestation and interoperability
  • formal verification
  • validation and performance evaluation of trusted hardware
  • supply chain security
  • threat analysis
  • abstractions and runtimes

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Published Papers (2 papers)

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Research

23 pages, 1262 KB  
Article
Confidential Kubernetes Deployment Models: Architecture, Security, and Performance Trade-Offs
by Eduardo Falcão, Fernando Silva, Carlos Pamplona, Anderson Melo, A S M Asadujjaman and Andrey Brito
Appl. Sci. 2025, 15(18), 10160; https://doi.org/10.3390/app151810160 - 17 Sep 2025
Cited by 1 | Viewed by 3065
Abstract
Cloud computing brings numerous advantages that can be leveraged through containerized workloads to deliver agile, dependable, and cost-effective microservices. However, the security of such cloud-based services depends on the assumption of trusting potentially vulnerable components, such as code installed on the host. The [...] Read more.
Cloud computing brings numerous advantages that can be leveraged through containerized workloads to deliver agile, dependable, and cost-effective microservices. However, the security of such cloud-based services depends on the assumption of trusting potentially vulnerable components, such as code installed on the host. The addition of confidential computing technology to the cloud computing landscape brings the possibility of stronger security guarantees by removing such assumptions. Nevertheless, the merger of containerization and confidential computing technologies creates a complex ecosystem. In this work, we show how Kubernetes workloads can be secured despite these challenges. In addition, we design, analyze, and evaluate five different Kubernetes deployment models using the infrastructure of three of the most popular cloud providers with CPUs from two major vendors. Our evaluation shows that performance can vary significantly across the possible deployment models while remaining similar across CPU vendors and cloud providers. Our security analysis highlights the trade-offs between different workload isolation levels, trusted computing base size, and measurement reproducibility. Through a comprehensive performance, security, and financial analysis, we identify the deployment models best suited to different scenarios. Full article
(This article belongs to the Special Issue Secure Cloud Computing Infrastructures)
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32 pages, 1473 KB  
Article
Strengthening Trust in Virtual Trusted Platform Modules: Integrity-Based Anchoring Mechanism for Hyperconverged Environments
by Marcela Santos and Reinaldo Gomes
Appl. Sci. 2025, 15(10), 5698; https://doi.org/10.3390/app15105698 - 20 May 2025
Viewed by 1646
Abstract
Virtual Trusted Platform Modules (vTPMs) are widely adopted in commercial cloud platforms such as VMware Cloud, Google Cloud, Microsoft Azure, and Amazon AWS. However, as software-based components, vTPMs do not provide the same security guarantees as hardware TPMs. The existing solutions attempt to [...] Read more.
Virtual Trusted Platform Modules (vTPMs) are widely adopted in commercial cloud platforms such as VMware Cloud, Google Cloud, Microsoft Azure, and Amazon AWS. However, as software-based components, vTPMs do not provide the same security guarantees as hardware TPMs. The existing solutions attempt to mitigate this limitation by anchoring vTPMs to physical TPMs, but such approaches often face challenges in heterogeneous environments and in failure recovery or migration scenarios. Meanwhile, the evolution of data center architectures toward hyperconverged infrastructures introduces new opportunities for security mechanisms by integrating compute, storage, and networking into a single solution. This work proposes a novel mechanism to securely anchor vTPMs in hyperconverged environments. The proposed approach introduces a unified software layer capable of aggregating and managing the physical TPMs available in the data center, establishing a root of trust for vTPM anchoring. It supports scenarios where hardware TPMs are not uniformly available and enables anchoring replication for critical systems. The solution was implemented and evaluated in terms of its performance impact. The results show low computational overhead, albeit with an increase in anchoring time due to the remote anchoring process. Full article
(This article belongs to the Special Issue Secure Cloud Computing Infrastructures)
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