Context-based copresence detection schemes are a necessary prerequisite to building secure and usable authentication systems in the Internet of Things (IoT). Such schemes allow one device to verify proximity of another device without user assistance utilizing their physical context (e.g., audio). The state-of-the-art copresence detection schemes suffer from two major limitations: (1) they cannot accurately detect copresence in low-entropy context (e.g., empty room with few events occurring) and insufficiently separated environments (e.g., adjacent rooms), (2) they require devices to have common sensors (e.g., microphones) to capture context, making them impractical on devices with heterogeneous sensors. We address these limitations, proposing Next2You, a novel copresence detection scheme utilizing channel state information (CSI). In particular, we leverage magnitude and phase values from a range of subcarriers specifying a Wi-Fi channel to capture a robust wireless context created when devices communicate. We implement Next2You on off-the-shelf smartphones relying only on ubiquitous Wi-Fi chipsets and evaluate it based on over 95 hours of CSI measurements that we collect in five real-world scenarios. Next2You achieves error rates below 4%, maintaining accurate copresence detection both in low-entropy context and insufficiently separated environments. We also demonstrate the capability of Next2You to work reliably in real-time and its robustness to various attacks.
翻译:以环境为基础的内心内分泌检测机制是建立互联网物质(IoT)系统安全和可用认证系统的必要先决条件。这种机制使一个装置能够核查另一个装置的距离,而没有使用其物理环境(例如音频)的用户协助,就可以核查另一个装置的距离。 最先进的共心探测机制存在两大限制:(1) 它们无法精确地检测低粒(例如,空室,发生的事件很少)和不完全分离的环境(例如,相邻房间)中的共存系统(例如,相邻房间)和不完全分离的环境(例如,相邻房间)中的共测系统,(2) 它们需要装置,以便拥有共同的传感器(如麦克风)来捕捉环境,使不同传感器的装置不切实际操作。 此类机制允许一种装置能够使用物理环境(例如音响音音)来核查另一个装置,即利用频道状态信息(CSI)来协助用户协助另一个装置。 特别是,我们利用一系列子容器的大小和阶段价值,具体指定一个W-Fi频道,以捕捉到设备通信所创建的强的无线环境。 我们用“LW2你”的外智能手机安装的智能手机安装的智能手机,只只只只只只能捕捕取环境捕取环境捕取环境,使使用我们五个WFFFF菲芯背景评估它,在下面以下环境下进行不及评估它。