Abstract
Compressive sensing (CS) is often utilized to encrypt data on resource constrained terminals due to its lightweight and confidentiality. However, due to its low security level, it cannot meet the security requirements when interacting with the cloud in a complex cloud environment. Therefore, the more complex and higher security encryption computing is migrated to the edge device, and CS is combined as a new image data security transmission framework. In terms of image data confidentiality, lightweight encryption based on CS is implemented on the terminal, and then the data is clustered into central data and residual data by the proposed clustering algorithm at the edge, and the central data is further encrypted with high strength. In terms of image data integrity, hash algorithm based on CS is used to verify the correctness of the reconstructed data, and the redundancy of Reed-solomon code (RS) is used to improve the tampering recovery capability of data transmitted between edge devices and cloud. Simulation results and analysis verify the security and applicability of our transmission framework.
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Acknowledgment
The work was supported by the National Key R&D Program of China (Grant No. 2020YFB1805400) and the National Natural Science Foundation of China (Grant No. 62072063).
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Zheng, H., Huang, Y., Li, L., Xiao, D. (2022). Compressive Sensing-Based Image Encryption and Authentication in Edge-Clouds. In: Þór Jónsson, B., et al. MultiMedia Modeling. MMM 2022. Lecture Notes in Computer Science, vol 13142. Springer, Cham. https://doi.org/10.1007/978-3-030-98355-0_32
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DOI: https://doi.org/10.1007/978-3-030-98355-0_32
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