Multitiered Reversible Data Privacy Protection Scheme for IoT Based on Compression Sensing and Digital Watermarking

Zhufeng Suo, Chao Xia, Donghua Jiang, Haipeng Peng, Fenghua Tong, Xiaoming Chen

Abstract: Privacy preservation and low-cost data processing have become two critical issues in the era of Internet of Things (IoT) due to the widespread deployment of lightweight smart surveillance and sensors. In this article, we propose a multitiered reversible data privacy preservation system based on compressive sensing (CS) and watermarking. The system anonymizes the region of interest (ROI) using an obfuscation matrix while compressing and encrypting the entire document. CS provides the first-tier encryption for data documents, and the obfuscation matrix provides the second-tier encryption for sensitive parts of data documents. The system offers a multitiered privacy protection scheme where restricted-authorized users can only access nonsensitive data while fully authorized users can access the entire document. To implement the reversible elimination of the obfuscation matrix, two watermark embedding methodologies are proposed in the CS domain in order. In both methods, the watermark generated by the obfuscation matrix is embedded in the encrypted CS measurement values, with the first methodology concentrating on the optimal data reconstruction quality and the second methodology working to balance storage space and data restoration quality. Extensive experimental results indicate the superiority of the proposed methodologies over other conventional reversible data privacy preservation schemes.