Secure Outsourced Principal Eigentensor Computation for Cyber-Physical-Social Systems

Abstract

Cyber-physical-social systems (CPSS) are revolutionizing the relationships between humans, computers and things. Outsourcing computation to cloud can offer resources-constrained enterprises and consumers sustainable computing in CPSS. However, ensuring the security of data in such an outsourced environment remains a research challenge. Principal eigentensor computation has emerged as a powerful tool dealing with multidimensional cyber-physical-social systems data. In this paper, we present two novel secure principal eigentensor computation (SPEC) schemes for sustainable CPSS. To the best of our knowledge, this is the first effort to address SPEC over encrypted data in cloud without the interaction need between multiple users and cloud. More specifically, we leverage cloud server and trusted hardware component to design a collaborative cloud model. Using the model, we propose (1) a basic SPEC scheme based on homomorphic computing and (2) an efficient SPEC scheme that combines the advantages of homomorphic computing and garbled circuits, and exploits packing technology to reduce computational cost. Finally, we theoretically and empirically analyze the security and efficiency of our SPEC schemes. Findings demonstrate that the proposed schemes provide a secure and efficient way of outsourcing computation for CPSS. In addition, from the cloud user's perspective, our proposal is lightweight.

Stylized image resolution enhancement scheme based on an improved convolutional neural network in cyber‐physical systems

“…As an emerging intelligence computing paradigm, edge computing based on intelligent techniques can accelerate content processing and improve the quality of services and applications in cyber‐physical systems (CPS) 1,2 . Thus, edge computing is attracting increasing attention from academia and industry because of its advantages in terms of throughput, delay, network scalability and processing ability 2,3 . Image style transfer has been a hot topic in the field of computer vision in recent years, which generates new migrating images from given content images and style images 3 .…”

“…1,2 Thus, edge computing is attracting increasing attention from academia and industry because of its advantages in terms of throughput, delay, network scalability and processing ability. 2,3 Image style transfer has been a hot topic in the field of computer vision in recent years, which generates new migrating images from given content images and style images. 3 In addition to its economic value, image style transfer can inherit and develop traditional paintings and provide some innovative abilities.…”