SemGuard: Toward Intrinsic Trusted Access Framework for Semantic Communication via Backdoor Regularization

Semantic Communication (SC) codecs contain valuable intellectual property, but current security is ineffective against model piracy. To address this, we propose SemGuard, an intrinsic trusted access framework that embeds a backdoor within the SC codec. Legitimate users use a credential generator to embed sample-specific credentials into inputs, activating the backdoor for seamless transmission. Conversely, unauthorized inputs lacking this credential are deliberately processed into anomalous outputs. This backdoor is implanted via a regularized joint training process. Even if the model is extracted, it remains functionless without credentials, effectively deterring illegitimate access without sacrificing efficiency, and preserving defensive efficacy in adversarial settings.