论文标题
Beehive：基于智能环境中对象交互的行为生物识别系统
BeeHIVE: Behavioral Biometric System based on Object Interactions in Smart Environments
论文作者
论文摘要
物联网（IoT）生态系统中缺乏标准输入界面提出了确保此类基础架构的挑战。为了应对这一挑战，我们基于与智能环境中对象的自然相互作用引入了一种新颖的行为生物识别系统。该生物特征利用现有的传感器来验证用户，而无需对现有智能家居设备进行任何硬件修改。该系统旨在减少对智能家居系统目前依赖的基于电话的身份验证机制的需求。它要求用户仅当无法通过与智能环境的互动来高度信心身份验证用户时批准手机上的交易。 我们进行了一个现实世界中的实验，该实验涉及公司环境中的13名参与者，还使用该实验研究了对我们提出的系统的模仿攻击。我们表明，该系统可以提供无缝且不引人注目的身份验证，同时仍然对零富特性，视频和基于亲自观察的模仿攻击保持高度抵抗。即使最大类型的模仿攻击最多1％成功，我们的系统也不要求用户拿出手机来批准80％以上的案例中的合法交易。当考虑与更多对象的相互作用时，这将增加到92％的交易。
The lack of standard input interfaces in the Internet of Things (IoT) ecosystems presents a challenge in securing such infrastructures. To tackle this challenge, we introduce a novel behavioral biometric system based on naturally occurring interactions with objects in smart environments. This biometric leverages existing sensors to authenticate users without requiring any hardware modifications of existing smart home devices. The system is designed to reduce the need for phone-based authentication mechanisms, on which smart home systems currently rely. It requires the user to approve transactions on their phone only when the user cannot be authenticated with high confidence through their interactions with the smart environment. We conduct a real-world experiment that involves 13 participants in a company environment, using this experiment to also study mimicry attacks on our proposed system. We show that this system can provide seamless and unobtrusive authentication while still staying highly resistant to zero-effort, video, and in-person observation-based mimicry attacks. Even when at most 1% of the strongest type of mimicry attacks are successful, our system does not require the user to take out their phone to approve legitimate transactions in more than 80% of cases for a single interaction. This increases to 92% of transactions when interactions with more objects are considered.
