Generative adversarial networks-based security and applications in cloud computing: a survey

Shiyu Wang (), Ming Yin, Yiwen Liu and Guofeng He
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Shiyu Wang: China Telecom Research Institute
Ming Yin: China Telecom Research Institute
Yiwen Liu: Donghua University
Guofeng He: China Telecom Research Institute

Telecommunication Systems: Modelling, Analysis, Design and Management, 2024, vol. 86, issue 2, No 6, 305-331

Abstract: Abstract To meet growing business needs and exponentially increasing development and maintenance costs, the concept of cloud computing has been proposed and developed rapidly. Cloud computing is a brand-new computing mode that can meet the needs of on-demand distribution and the rapid deployment of computing resources. It can provide strong scalability and applicability through virtualisation technology and elastic technology, and it can adapt to the needs of users in different environments and resources. Through the use of hardware such as cloud sensors, the data collected by various types of sensors can be directly uploaded to the cloud for processing and analysis, so that applications such as management, medical treatment and human–machine cooperation can be provided. However, applications in the cloud have upended traditional security boundaries and will face some unique security challenges. Due to the advantages of generating real data, generative adversarial networks (GANs) have attracted extensive attention in the field of cloud computing, such as data augmentation and encryption. Therefore, this paper reviews GAN-based security and applications in cloud computing. We compare the role of GANs in security and applications in the cloud from multiple dimensions. In addition, we analyse the research trends and future work prospects from the perspective of the algorithm itself, algorithm performance evaluation and cloud computing hardware.

Keywords: Generative adversarial networks; Data augmentation; Cloud computing; Security; Application (search for similar items in EconPapers)
Date: 2024
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DOI: 10.1007/s11235-024-01166-x

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