Secure Joint Source-Channel Coding of Multimodal Semantic Sources
It provides a theoretical framework for secure communication of multimodal data, which is relevant for applications like distributed sensor networks.
The paper extends the rate-distortion-perception problem to multimodal sources transmitted over wiretap channels, establishing bounds on the fundamental limits of rate, distortion, and secrecy under per-modality constraints.
We study the problem of secure joint source-channel coding for multimodal semantic sources transmitted over noisy wiretap channels. The source model consists of $m$ modalities (e.g., image, audio, and sensor data), all represented as random variables. The encoder observes independent and identically distributed samples of an arbitrary non-empty subset of modalities. The samples are encoded and transmitted over a discrete memoryless wiretap channel. The legitimate receiver reconstructs all modalities. We extend the rate-distortion-perception problem formulation to multimodal sources. We establish converse and achievability bounds on the fundamental limits of transmission rate, fidelity, and secrecy, under per-modality distortion and perception constraints, and per-subset equivocation constraints. We show that the fundamental limit for secrecy consists of three operationally distinct components: the level of compression, the secret key rate, and the statistics of the wiretap channel.