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A Secure and Efficient Image Sharing Method Based on Bilateral Compressive Sensing With Multilevel Privacy Preserving Function
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Summary
Researchers propose an image sharing method based on bilateral compressive sensing that provides multilevel privacy preservation. Data owners compress original images with designed measurement matrices using the proposed T ℓ1-B2DLDA algorithm, producing dimension-reduced data that supports classification for level I data users and reconstruction for level II data users. Level I users can complete their tasks without obtaining private or confidential information from the original images. The paper reports experiments on feasibility, performance and robustness, plus theoretical and practical security analysis, and releases its source code publicly.