Ensuring the trustworthiness of data from distributed and resource-constrained environments, such as Wireless Sensor Networks or IoT devices, is critical. Existing Reversible Data Hiding (RDH) methods for scalar data suffer from low embedding capacity and poor intrinsic mixing between host data and watermark. This paper introduces Hiding in the Imaginary Domain with Data Encryption (H[i]dden), a novel framework based on complex number arithmetic for simultaneous information embedding and encryption. The H[i]dden framework offers perfect reversibility, in-principle unlimited watermark size, and intrinsic data-watermark mixing. The paper further introduces two protocols: H[i]dden-EG, for joint reversible data hiding and encryption, and H[i]dden-AggP, for privacy-preserving aggregation of watermarked data, based on partially homomorphic encryption. These protocols provide efficient and resilient solutions for data integrity, provenance and confidentiality, serving as a foundation for new schemes based on the algebraic properties of the complex domain.

翻译：确保来自分布式及资源受限环境（如无线传感器网络或物联网设备）数据的可信性至关重要。现有面向标量数据的可逆数据隐藏方法存在嵌入容量低、宿主数据与水印内在混合性差的问题。本文提出基于复数运算的H[i]dden框架，实现信息嵌入与加密的同步处理。该框架具备完全可逆性、理论上无限的水印容量以及数据与水印的内在混合特性。本文进一步提出两种协议：基于部分同态加密的H[i]dden-EG协议用于可逆数据隐藏与加密的联合处理，H[i]dden-AggP协议用于带水印数据的隐私保护聚合。这些协议为数据完整性、溯源性和机密性提供了高效稳健的解决方案，为基于复数域代数特性的新型方案奠定了理论基础。