• Propose two ( k, n )-threshold RDHEI schemes fusing EMD and PSIS, solving poor fault-tolerance and separability in existing schemes. • Eliminate location map overhead via EMD, boosting embedding payload and simplifying the framework. • Achieve high performance, with embedding rate up to 2 bpp, PSNR > 53 dB, SSIM > 0.99 (EMD-RDHP scheme) and lossless recovery (Modified EMD-RDHP scheme). • Avoid complex computations while ensuring security, fitting secure cloud storage and multi-party collaboration. With the development of cloud computing and related technologies, Reversible Data Hiding in Encrypted Image (RDHEI) has emerged as a privacy-preserving technique that enables embedding additional data into cover image while ensuring its confidentiality. However, most existing RDHEI schemes rely on a single encrypted image, lacking fault-tolerance for both image reconstruction and data extraction. Additionally, many schemes suffer from high computational complexity and the separability of image reconstruction and data extraction. To address these limitations, in this paper, we propose two novel ( k, n )-threshold RDHEI schemes by combining Exploiting Modification Direction (EMD) and polynomial-based secret image sharing (PSIS) techniques, achieving fault-tolerance for both image and embedded data, while improving embedding capacity and supporting lossless recovery. The first scheme, EMD-based Reversible Data Hiding with Polynomial (EMD-RDHP) scheme, employs PSIS to share the secret image and embeds secret data during the sharing process using EMD. This approach achieves high embedding capacity and high-quality image reconstruction (PSNR > 53 dB, SSIM > 0.99). However, it introduces slight distortion, failing to losslessly recover the secret image. To address this limitation, we further propose a Modified EMD-RDHP scheme, which records pixel modification operation in the polynomial coefficients, enabling lossless reconstruction of the secret image. Both proposed schemes support independent data extraction and image reconstruction, ensuring their separability. Experimental results demonstrate that the proposed schemes outperform existing methods in terms of fault-tolerance, embedding capacity, and computational efficiency.

Existing Reversible Data Hiding in Encrypted Domain (RDH-ED) frameworks primarily focus on the fault tolerance of cover images and the execution sequence of embedding space release and encryption operations. However, most existing schemes suffer from a single-point failure issue during secret data extraction, and their data embedding capacity is constrained by the texture features of cover images. To address these limitations, this paper proposes a general RDH-ED framework supporting multiple data hiders, based on secret sharing and Hamming codes. The proposed framework employs polynomial-based secret sharing on both the cover image and the secret data separately. Specifically, the polynomial coefficients for cover image sharing consist of three components: Hamming codes, the differences between image pixel values and corresponding Hamming codes, and random numbers; in contrast, the polynomial coefficients for secret data sharing are generated by combining check codes and random numbers. By leveraging the additive homomorphic property of polynomial sharing over the finite field GF(2⁸), secret data shares are linearly embedded into cover image shares. Theoretical analyses and experimental results demonstrate that, by exploiting the error-correcting capability of Hamming codes, the proposed scheme achieves complete recovery of the cover image and lossless extraction of the secret data, with a maximum data embedding rate of 6.857 bits per pixel for 8-bit grayscale images. Furthermore, the scheme exhibits fault tolerance in both image recovery and data extraction. Moreover, the embedding capacity is independent of the cover image's texture features, which enhances its adaptability to diverse scenarios such as multi-user cloud storage and distributed secure communication.

Searchable encryption has garnered considerable attention for its ability to empower users to perform searches on encrypted data stored remotely without compromising confiden-tiality. Multi-source multi-client (M/M) searchable symmetric encryption excels in efficiently outsourcing and sharing data from multiple data sources, making it ideal for cloud-IoT applications with numerous terminal devices. However, empirical analysis shows that the recently proposed M/M scheme, despite being potentially the most representative scheme currently available, still confronts two primary challenges. First, it only supports single keyword searches, which constrains its applicability in more complex query scenarios. Second, it focuses exclusively on forward privacy but neglects backward privacy, potentially leaving sensitive information vulnerable during dynamic data updates. To tackle these issues, we propose a new multi-source multi-client conjunctive searchable encryption (MMCSE) scheme, which enables non-interactive conjunctive searches while ensur-ing both forward and backward privacy. Building on this foun-dation, we further bolster security and functionality with the enhanced scheme named eMMCSE. By leveraging puncturable pseudorandom functions and n-dimensional dynamic symmetric hidden vector encryption (n-DSHVE), eMMCSE effectively minimizes result pattern leakage and provides the revocation mechanism, supporting both coarse-grained revocation of specific clients and fine-grained revocation of particular records. The security analysis demonstrates that the proposed schemes are secure against the adversarial server and colluding clients. Addi-tionally, experimental results highlight their marked enhance-ments in search efficiency across most scenarios.

Quick Response (QR) code, a machine-readable symbol, is widely employed in all walks of life due to its large information capacity, strong error correction ability, and fast reading speed. However, anyone with a standard decoder could obtain stored information. In this paper, utilizing the characteristics of the Hamming code, wet paper code, and the recognition mechanism of the QR code, we introduce a high-capacity QR code with three-layer information to protect the sensitive information. In the proposed scheme, we utilize the XOR-based secret-sharing algorithm to embed the second-layer information on the column vector of the constructed random matrix block. Then, without affecting the embedding result of the second layer information, the matrix block elements are reused again, and the Hamming code is constructed with the column vector. Based on the error correction mechanism of the Hamming code, the third layer of information is embedded on the column vector and encoded by wet paper coding to realize the blind extraction. Finally, based on the recognition mechanism of the QR code, the random matrix block containing the secret information is fused with the carrier QR code, and the public information of the carrier QR code is used as the first-layer information. Compared with other schemes, the proposed scheme has the advantages of high information payload, low computational complexity, and strong robustness.

Quick response (QR) codes have been widely used in applications, such as data storage and high-speed machine reading. Anyone can gain access to the information stored in QR codes; therefore, they are unsuitable for encoding secret information without the addition of cryptography or other protection. In this paper, we propose a visual secret sharing scheme to encode a secret QR code into several shares. In contrast with other techniques, the shares in our scheme are valid QR codes that can be decoded with some specific meaning by a standard QR code reader, thereby avoiding raising suspicion in potential attackers. Moreover, the secret message is recovered by XOR-ing the qualified shares, an operation that can easily be performed using smartphones or other QR scanning devices. Experimental results show that the proposed scheme is both feasible and reasonably secure. Our scheme's high sharing efficiency is also highlighted in this paper.