Positional Information Leakage of Wireless Consumer Electronic Devices

智能手机和其他便携式设备不断发出信号，用于与Wi-Fi、蓝牙和4G/5G通信。在过去的工作中，这些排放已被证明可以揭示用户的位置和身份。这带来了隐私风险，因为用户的移动可能会被企业出于营销和分析目的或攻击者出于更恶意的原因而跟踪。目前的对策包括探测Wi-Fi网络时的MAC地址随机化，或在位置之间移动时手动更改MAC地址。然而，这可能不足以防止识别时，信号指纹识别方法被用来唯一地识别一个设备，而不考虑的数据内容的transmission.My研究的目的是探讨有关的问题，身份信息泄漏和细粒度本地化使用消费电子设备使用商业现货（COTS）硬件。我主要关注的是利用智能手机天线的辐射模式来了解设备的更多信息，而不仅仅是一个粗略的位置。智能手机的天线方向图可用于基于独特的信号强度方向图来识别设备，并通过将当前的信号强度测量值映射到先前测量的天线方向图来确定它们的方向并了解更多关于它们的细颗粒运动的信息。这些攻击方法还有待探索，并造成严重的隐私问题，使现有的跟踪对策无效，我将寻求开发一系列新的对策，以防止这种隐私风险。Wi-Fi发射将成为焦点，因为传输功率相对较高，这使得它们可以在比蓝牙更远的距离上进行测量，并且与LTE和5G不同，使用廉价的COTS硬件和开源软件很容易收集和处理。不安全的物联网（IoT）设备会带来特殊的风险，因为它们提供了一个可能的平台来进行这类攻击。虽然存在明显的风险，但也有潜在的合法用途来提高安全性，例如未经授权的设备/人员入侵检测到安全空间。该项目福尔斯EPSRC数字经济研究领域和安全，隐私和信任子主题。

Smartphones and other portable devices continuously emit signals for communication with Wi-fi, Bluetooth, and 4G/5G. In the past work these emissions have been shown to reveal the location and identity of users. This presents privacy risks as a user's movement can be tracked overtime by business for marketing and analytics purposes or attackers for more malicious reasons. Current countermeasures include MAC address randomisation when probing for wi-fi networks or manually changing MAC addresses when moving between locations. However, this may not be sufficient to prevent identification when signal fingerprinting methods are used to uniquely identify a device without considering the data content of the transmission.My research aims to explore issues related to identity information leakage and fine grained localisation using consumer electronic devices using commercial-off-the-shelf (COTS) hardware. My main focus is on the potential to exploit the radiation pattern of smartphone antennae to learn more about a device than simply a rough location. The antenna patterns of smartphones could be used to identify devices based on unique signal strength patterns and determine their orientation and learn more about their fine grain movement by mapping current signal strength measurements to previously measured antenna patterns. These attack methods are yet to be explored and pose severe privacy issues rendering existing tracking countermeasures ineffective and I will look to develop a new range of countermeasures to protect against this privacy risks. Wi-fi emissions will be the focal point as the power of transmissions are relatively high which makes them measurable over larger distances than Bluetooth and are very easy to collect and process using cheap COTS hardware and opensource software unlike LTE and 5G. Insecure Internet of Things (IoT) devices present a particular risk because they provide a possible platform from which to conduct these kinds of attacks. Although there are clear risks, there are a potentially legitimate uses for improving security, such as intrusion detection of unauthorised devices/people into secure spaces.This project falls within the EPSRC Digital economy research area and the Security, privacy, and trust sub theme.