Secure Joint Source-Channel Coding of Multimodal Semantic Sources

TL;DR

This paper investigates secure joint source-channel coding for multimodal semantic data over noisy wiretap channels, establishing fundamental limits involving compression, secrecy, and perception constraints.

Contribution

It extends the rate-distortion-perception framework to multimodal sources and derives bounds on transmission rate, fidelity, and secrecy for such complex sources.

Findings

Established converse and achievability bounds for multimodal sources.

Identified three key components of secrecy: compression, secret key rate, and channel statistics.

Extended the rate-distortion-perception problem to multiple modalities.

Abstract

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.