A framework that perturbs private semantic representations with learnable DP noise via GAN inversion and adversarial training to secure image SemCom over wiretap channels with tunable privacy levels.
Intellicise wireless networks from semantic communications: A survey, research issues, and challenges,
3 Pith papers cite this work. Polarity classification is still indexing.
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UNVERDICTED 3representative citing papers
A parametric memory network reconstructs truncated semantic tokens from prefixes in wireless communication, outperforming benchmarks by up to 1.09 dB PSNR.
A structured review organizing fundamentals, shared and digital-specific threats, defenses, and open directions for secure digital semantic communications.
citing papers explorer
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Privacy-Preserving Semantic Communication over Wiretap Channels with Learnable Differential Privacy
A framework that perturbs private semantic representations with learnable DP noise via GAN inversion and adversarial training to secure image SemCom over wiretap channels with tunable privacy levels.
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Evolving Token Communication with Parametric Memory Network
A parametric memory network reconstructs truncated semantic tokens from prefixes in wireless communication, outperforming benchmarks by up to 1.09 dB PSNR.
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Secure Digital Semantic Communications: Fundamentals, Challenges, and Opportunities
A structured review organizing fundamentals, shared and digital-specific threats, defenses, and open directions for secure digital semantic communications.