Deploying Testbed Docker-based application for Encryption as a Service in Kubernetes

The scalability of today’s networking infrastructures, such as Kubernetes, has increased the demand for everything-as-a-service concepts, including encryption services. This paper details deploying an Encryption as a Service (EaaS) framework on Kubernetes. In our current implementation, a web platform is dedicated to the subscription processes and managing the requested services. Service providers subscribe to receive encryption and decryption services for their clients, and a token is assigned to them. The client, or better to say, the devices covered by that service provider, can use encryption/decryption to specify that token. As our implemented web platform is written in Django, through this paper, we have discussed the deployment of Django applications on Kubernetes and the role of two other services (i.e., Database and Nginx) to make it available. The services are executed on Docker containers and deployed on Kubernetes pods. We have also explained the steps to build Docker containers, including the details of Dockerfiles. We have deployed this framework on both local and remote Kubernetes environments. The former deployment was performed by setting up a local Minikube cluster, while the latter assumes a remote Kubernetes cluster, and we are connecting to it through a VPN. We have tested the availability and accuracy of the encryption/decryption services and checked the logs to ensure that these services work correctly. We aim to present this article to assist researchers wishing to conduct effective testing or a Testbed in the real world.

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Publication Details

Published
2024-09-26
DOI
https://doi.org/10.23919/softcom62040.2024.10721658
Citations
8
Primary Topic
Advanced Malware Detection Techniques
Type
article
Field-Weighted Citation Impact
2.80

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article

Deploying Testbed Docker-based application for Encryption as a Service in Kubernetes

Luís Cordeiro, Amir Javadpour, Forough Ja’fari, Chafika Benzaïd et al.
8 citations
Advanced Malware Detection Techniques
2.80
article

Deploying Testbed Docker-based application for Encryption as a Service in Kubernetes

Luís Cordeiro, Amir Javadpour, Forough Ja’fari, Chafika Benzaïd, Tarik Taleb, Pedro R. Tomas, Luis Rosa
article en
8 citations

Abstract

The scalability of today’s networking infrastructures, such as Kubernetes, has increased the demand for everything-as-a-service concepts, including encryption services. This paper details deploying an Encryption as a Service (EaaS) framework on Kubernetes. In our current implementation, a web platform is dedicated to the subscription processes and managing the requested services. Service providers subscribe to receive encryption and decryption services for their clients, and a token is assigned to them. The client, or better to say, the devices covered by that service provider, can use encryption/decryption to specify that token. As our implemented web platform is written in Django, through this paper, we have discussed the deployment of Django applications on Kubernetes and the role of two other services (i.e., Database and Nginx) to make it available. The services are executed on Docker containers and deployed on Kubernetes pods. We have also explained the steps to build Docker containers, including the details of Dockerfiles. We have deployed this framework on both local and remote Kubernetes environments. The former deployment was performed by setting up a local Minikube cluster, while the latter assumes a remote Kubernetes cluster, and we are connecting to it through a VPN. We have tested the availability and accuracy of the encryption/decryption services and checked the logs to ensure that these services work correctly. We aim to present this article to assist researchers wishing to conduct effective testing or a Testbed in the real world.

Sharif University of Technology (IR), OneSource (Portugal) (PT), Ruhr University Bochum (DE), University of Oulu (FI)
Academy of Finland, HORIZON EUROPE Framework Programme
Openalex Percentile: Top 8%
Advanced Malware Detection Techniques
2.80
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