Generative AI-aided Joint Training-free Secure Semantic Communications via Multi-modal Prompts

• URL: http://arxiv.org/abs/2309.02616v1
• Date: Tue, 5 Sep 2023 23:24:56 GMT
• Title: Generative AI-aided Joint Training-free Secure Semantic Communications via Multi-modal Prompts
• Authors: Hongyang Du, Guangyuan Liu, Dusit Niyato, Jiayi Zhang, Jiawen Kang, Zehui Xiong, Bo Ai, and Dong In Kim
• Abstract summary: This paper proposes a GAI-aided SemCom system with multi-model prompts for accurate content decoding. In response to security concerns, we introduce the application of covert communications aided by a friendly jammer.
• Score: 89.04751776308656
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: Semantic communication (SemCom) holds promise for reducing network resource consumption while achieving the communications goal. However, the computational overheads in jointly training semantic encoders and decoders-and the subsequent deployment in network devices-are overlooked. Recent advances in Generative artificial intelligence (GAI) offer a potential solution. The robust learning abilities of GAI models indicate that semantic decoders can reconstruct source messages using a limited amount of semantic information, e.g., prompts, without joint training with the semantic encoder. A notable challenge, however, is the instability introduced by GAI's diverse generation ability. This instability, evident in outputs like text-generated images, limits the direct application of GAI in scenarios demanding accurate message recovery, such as face image transmission. To solve the above problems, this paper proposes a GAI-aided SemCom system with multi-model prompts for accurate content decoding. Moreover, in response to security concerns, we introduce the application of covert communications aided by a friendly jammer. The system jointly optimizes the diffusion step, jamming, and transmitting power with the aid of the generative diffusion models, enabling successful and secure transmission of the source messages.

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