Thwarting Wi-Fi Side-Channel Analysis through Traffic Demultiplexing

通过流量解复用阻止 Wi-Fi 侧信道分析

• 批准号: 418521-2012
• 负责人: He, Wenbo
• 金额: $ 1.6万
• 依托单位: McGill University
• 依托单位国家: 加拿大
• 项目类别: Discovery Grants Program - Individual
• 财政年份: 2015
• 资助国家: 加拿大
• 起止时间: 2015-01-01 至 2016-12-31
• 项目状态: 已结题
• 来源: https://www.nserc-crsng.gc.ca/ase-oro/Details-Detailles_eng.asp?id=573703
• 关键词: Thwarting; Wi; Fi; Side; Channel

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.

Wi-Fi网络得到广泛部署。在Wi-Fi网络中，即使对流量进行加密，也不可避免地会在无线链路上产生侧信道信息泄漏，因为通过流量分析可以识别流量流的特征。作为一个序列，在各种在线应用程序中已经报道了侧信道信息泄漏。然而，Wi-Fi网络仍然严重缺乏有效的解决方案来减少信息泄露。