The lack of standard input interfaces in Internet of Things (IoT) ecosystems presents a challenge in securing such infrastructure. To tackle this challenge, we introduce a novel behavioural biometric system based on naturally occurring interactions with objects in smart environments. This biometric leverages existing sensors to authenticate users in such environments 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 our 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.
翻译:在Tings Internet(IoT)生态系统中缺乏标准输入界面是保障这类基础设施的一个挑战。为了应对这一挑战,我们引入了一个基于与智能环境中的物体自然发生相互作用的新式行为生物鉴别系统。这个生物鉴别系统利用了现有传感器,在不要求对现有智能家用设备作任何硬件修改的情况下,对此类环境中的用户进行认证,而无需对现有智能家用设备进行任何硬件改造。这个系统旨在减少对手机认证机制的需求,而智能家用系统目前依赖这种机制。它要求用户只有在用户无法通过与智能环境的相互作用获得高度信任认证的情况下,才能批准其手机上的交易。我们进行了一个现实世界实验,涉及13个公司环境中的参与者,同时利用这一实验研究对拟议系统进行模拟攻击。我们显示,我们的系统可以提供无缝和不受干扰的认证,同时仍然对零动能、视频和人间观测的模拟攻击保持高度抗力。即使最强的模拟攻击类型中最多只有1%的成功,但我们的系统也不要求用户拿出其手机来批准80%以上的合法交易,用于单一互动。这增加了交易的92%。