Thwarting Wi-Fi Side-Channel Analysis through Traffic Demultiplexing

Wi-Fi网络已被广泛部署。在Wi-Fi网络中，即使流量被加密，无线链路上的侧信道信息泄漏也是不可避免的，因为流量流的特征可以通过流量分析来识别。作为一个序列，侧信道信息泄漏已经在各种在线应用中被报道。然而，严重缺乏有效的解决方案来减轻Wi-Fi网络中的信息泄漏。 在这项研究中，我们将提出一种新的设计，称为流量解复用，以实现有效和高效的防御流量分析。我们的想法是将Wi-Fi流量流划分为片段，每个片段由流中的数据包的子集组成，当通过Wi-Fi信道传输这些数据包时。这可以防止攻击者重新组装片段以重建原始流的流量特征。我们的设计旨在提供一个有效的防御流量分析没有明显的网络性能下降。为此，我们将开发一种MAC层流量划分方法，包括MAC层虚拟化和多个虚拟MAC接口上的动态分组调度。以这种方式，单个虚拟接口的流量特性变得与原始流的流量特性显著不同，并且看起来独立于由其他接口产生的流量特性，从而为窃听者的流量分析增加了足够的挑战。 该研究将显著改善传统的无线链路上的流量分析防御。它将推进当今的应用程序开发实践，并将增强未来的无线通信标准。

Wi-Fi networks have been widely deployed. In Wi-Fi networks, even if the traffic is encrypted, the side-channel information leak over wireless links is inevitable, because the characteristics of traffic flows are identifiable through traffic analysis. As a sequence, side-channel information leaks have been reported in various online applications. However, a serious lack of efficient and effective solutions to mitigate information leaks persists in the Wi-Fi networks. In the proposed research, we will present a novel design, called traffic demultiplexing to achieve both effective and efficient defense against traffic analysis. Our idea is to partition a Wi-Fi traffic flow into snippets, each composed of a subset of the packets in the flow, when transmitting these packets through the Wi-Fi channel. This prevents adversaries from re-assembling the snippets to reconstruct the traffic characteristics of the original flow. Our design aims at providing an effective defense against traffic analysis without noticeable network performance degradation. To this end, we will develope a MAC layer traffic partition approach that includes MAC layer virtualization and dynamic packet scheduling over multiple virtual MAC interfaces. In this way, the traffic characteristics of a single virtual interface become significantly different from those of the original flow, and appear independent from those produced by other interfaces, thereby add enough challenges for traffic analysis by the eavesdropper. The proposed research will significantly improve the traditional defense against traffic analysis over the wireless links. It will advance today's application development practice with privacy concerns and will enhance future wireless communication standards.