Title: Wireless Image Transmission with Semantic and Security Awareness Show Chinese title

Title: 无线图像传输中的语义与安全意识

Abstract: Semantic communication is an increasingly popular framework for wireless image transmission due to its high communication efficiency. With the aid of the joint-source-and-channel (JSC) encoder implemented by neural network, semantic communication directly maps original images into symbol sequences containing semantic information. Compared with the traditional separate source and channel coding design used in bitlevel communication systems, semantic communication systems are known to be more efficient and accurate especially in the low signal-to-the-noise ratio (SNR) regime. This thus prompts an critical while yet to be tackled issue of security in semantic communication: it makes the eavesdropper more easier to crack the semantic information as it can be decoded even in a quite noisy channel. In this letter, we develop a semantic communication framework that accounts for both semantic meaning decoding efficiency and its risk of privacy leakage. To achieve this, targeting wireless image transmission, we on the one hand propose an JSC autoencoder featuring residual for efficient semantic meaning extraction and transmission, and on the other hand, propose a data-driven scheme that balances the efficiency-privacy tradeoff. Extensive experimental results are provided to show the effectiveness and robustness of the proposed scheme. Show Chinese abstract

Abstract: 语义通信由于其高效的通信效率，已成为无线图像传输日益流行的框架。 借助由神经网络实现的联合信源信道（JSC）编码器，语义通信直接将原始图像映射为包含语义信息的符号序列。 与传统比特级通信系统中使用的分离信源和信道编码设计相比，语义通信系统在低信噪比（SNR）区域被认为更高效且更准确。 因此，这引发了一个关键但尚未解决的安全问题：由于语义信息即使在非常嘈杂的信道中也可以被解码，这使得窃听者更容易破解语义信息。 在本文中，我们开发了一个考虑语义含义解码效率及其隐私泄露风险的语义通信框架。 为了实现这一目标，针对无线图像传输，一方面我们提出了一种具有残差特征的JSC自编码器，以实现高效的语义含义提取和传输，另一方面，我们提出了一种数据驱动的方案，以平衡效率与隐私之间的权衡。 提供了广泛的实验结果，以展示所提出方案的有效性和鲁棒性。