发表机构
School of Cyber Science and Engineering, Southeast University; University of Liverpool; School of Information Science and Engineering, Southeast University; School of Computer Science and Engineering, Nanyang Technological University（东南大学网络空间安全学院; 利物浦大学; 东南大学信息科学与工程学院; 南洋理工大学计算机科学与工程学院）
机构由 AI 辅助整理，请以论文原文为准。AI 中文总结
本文提出一种协议无关的物理层信息隐藏方法，利用编码器-解码器神经网络在前导码中嵌入秘密，并通过仿真到现实微调应对实际挑战，在LoRa和BLE上验证了可行性。
AI 中文摘要
物理层（PHY）信息隐藏支持关键应用，例如用于发射机识别的数字指纹识别和用于隐蔽通信的不可检测侧信道，并已引起研究界的广泛关注。先前研究的一类侧重于理论分析，提出诸如人工噪声或可重构智能表面等技术以实现不可检测的隐蔽传输。然而，由于算法复杂性或难以满足的假设，硬件原型很少被展示。另一类研究侧重于系统级解决方案，通过定制现有调制方案来实现物理层信息隐藏。然而，这些方法通常针对特定无线协议设计，限制了其通用性。在这项工作中，我们引入了一种新的物理层信息隐藏范式，与前述两类方法根本不同。受图像信息隐藏等其他领域最新进展的启发，我们将编码器-解码器神经网络迁移到物理层信息隐藏领域，通过在前导码波形中引入不可感知的失真来嵌入秘密。此外，我们提出了仿真到现实的微调以应对独特挑战，例如衰落和硬件缺陷。所设计的方法实用且协议无关。我们提供了两种商业流行无线技术（即LoRa和蓝牙低功耗（BLE））的案例硬件原型，使用商用软件定义无线电（SDR）收发器，展示了优异的可行性和通用性。
英文摘要
Physical layer (PHY) information hiding supports critical applications, such as digital fingerprinting for transmitter identification and undetectable side channels for covert communication, and has attracted considerable attention from the research community. One category of prior studies focuses on theoretical analysis, proposing techniques such as artificial noise or reconfigurable intelligent surfaces to enable undetectable covert transmission. However, hardware prototypes are rarely presented due to their algorithmic complexity or hard-to-satisfy assumptions. Another category of studies focuses on system-level solutions, achieving PHY information hiding by customizing existing modulation schemes. However, these methods are typically designed for specific wireless protocols, limiting their generalizability. In this work, we introduce a new PHY information hiding paradigm that differs fundamentally from the previous two categories of approaches. Inspired by recent advancements in other domains such as image information hiding, we migrate encoder-decoder neural networks to the PHY information hiding field, embedding secrets by introducing imperceptible distortions within the preamble waveform. Sim-to-real fine-tuning is additionally proposed to tackle unique challenges, e.g., fading and hardware imperfections. The designed methodology is practical and protocol-agnostic. We provide case hardware prototypes of two commercially popular wireless technologies, i.e., LoRa and Bluetooth Low Energy (BLE), using commodity software-defined radio (SDR) transceivers, demonstrating excellent feasibility and generalizability.
