Google Home Pcap

Smart speakers and voice-based virtual assistants are core components for the success of the IoT paradigm. Unfortunately, they are vulnerable to various privacy threats exploiting machine learning to analyze the generated encrypted traffic. To cope with that, deep adversarial learning approaches can be used to build black-box countermeasures altering the network traffic (e.g., via packet padding) and its statistical information.

智能音箱和基于语音的虚拟助手是物联网范式成功的关键组成部分。遗憾的是，它们容易受到各种利用机器学习分析生成加密流量的隐私威胁的侵害。为了应对这一问题，可以利用深度对抗学习的方法构建黑盒式防御措施，以改变网络流量（例如，通过数据包填充）及其统计信息。