论文标题
MusicID：用于物联网的基于脑电波的用户身份验证系统
MusicID: A Brainwave-based User Authentication System for Internet of Things
论文作者
论文摘要
我们提出了MusicID，这是一种使用音乐引起的脑电波模式作为行为生物识别模式的智能设备的身份验证解决方案。我们使用从真实用户收集的数据来评估MusicID，同时他们正在听两种形式的音乐。一首流行的英语歌曲和个人最喜欢的歌曲。我们表明，通过使用从4电极商品脑电波耳机收集的数据来实现用户识别的98％以上的精度，并且用户验证的精度超过97％。我们进一步表明，单电极能够提供约85％的精度，并且使用两个电极的精度约为95％。正如商品脑敏感性耳机用于冥想应用所显示的那样，我们认为在智能头部组合中包括干燥的脑电图电极是可行的，MusicID具有为即将到来的智能设备激增的入口点和连续身份验证框架提供的潜力，主要由增强现实（AR）/虚拟现实（VR）应用程序驱动。
We propose MusicID, an authentication solution for smart devices that uses music-induced brainwave patterns as a behavioral biometric modality. We experimentally evaluate MusicID using data collected from real users whilst they are listening to two forms of music; a popular English song and individual's favorite song. We show that an accuracy over 98% for user identification and an accuracy over 97% for user verification can be achieved by using data collected from a 4-electrode commodity brainwave headset. We further show that a single electrode is able to provide an accuracy of approximately 85% and the use of two electrodes provides an accuracy of approximately 95%. As already shown by commodity brain-sensing headsets for meditation applications, we believe including dry EEG electrodes in smart-headsets is feasible and MusicID has the potential of providing an entry point and continuous authentication framework for upcoming surge of smart-devices mainly driven by Augmented Reality (AR)/Virtual Reality (VR) applications.
