Flexible Visually Meaningful Image Transmission Scheme in WSNs Using Fourier Optical Speckle-Based Compressive Sensing.

Wireless sensor networks (WSNs) comprised of resource-limited devices face challenges related to network congestion and security threats. In this regard, this study introduces a groundbreaking approach called P-tensor product Fourier optical speckle-based compressive sensing (PTP-FOSCS) for image encryption. Primarily, to augment the scheme’s sensitivity to plaintext information, the parameters for the scrambling encryption were derived using the original image’s SHA-256 hash. Subsequently, the measurement matrix of the compressive sensing (CS) was constructed by capitalizing on the intrinsic randomness offered by Fourier optical speckle. The incorporation of P-tensor product (PTP) theory played a pivotal role by circumventing the conventional hurdle of dimension matching in matrix multiplication, thereby greatly improving the scheme’s flexibility and reducing its storage burden. Furthermore, the optical image encryption offers expeditious and parallel data processing capabilities, making it suitable for integration with CS for encrypting two images simultaneously to improved security and enhanced efficiency within the encryption system. Ultimately, the ciphertext image was discreetly embedded within a carrier image utilizing information hiding technology, which effectively masked the presence of encrypted information, thereby preventing visual suspicion from potential attackers. Empirical validation and comprehensive data corroborate the feasibility and security of the proposed methodology, which has a total key space of approximately 2572. It effectively withstands BFA, statistical attacks, CPA, among others. Furthermore, the novel measurement matrix significantly reduces data storage requirements and achieves higher-quality image reconstruction compared to classical alternatives applied in CS.