计算机科学 ›› 2025, Vol. 52 ›› Issue (1): 412-419.doi: 10.11896/jsjkx.231100076
• 信息安全 • 上一篇
苏超然, 张大龙, 黄勇, 董安
SU Chaoran, ZHANG Dalong, HUANG Yong, DONG An
摘要： 射频指纹利用射频前端的硬件特征作为标识符对设备进行识别。针对现有射频指纹识别研究忽略接收机硬件特性的干扰,导致模型在不同接收机设备上泛化性较差的问题,提出一种基于SE(Squeeze-and-Excitation)注意力多源域对抗网络的射频指纹识别方法。该方法采用多个源域有标签数据和少量目标域无标签数据进行对抗训练以提取与接收机域无关的特征;融合SE注意力机制增强模型对发送机射频指纹特征的学习能力;结合极少量目标域有标签数据对模型参数进行微调,进一步提高发送机识别性能。在Wisig公开数据集上的实验结果表明:该方法在跨接收机场景下可有效识别发送机设备,平均准确率可达83.1%;加入少量有标签数据微调后平均准确率可进一步提高至93.1%。
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