Thwarting Wi-Fi Side-Channel Analysis through Traffic Demultiplexing

点击翻译按钮获取中文摘要

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.