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Securing Smart Homes using a Behavior Analysis based Authentication Approach

机译:使用基于行为分析的身份验证方法来保护智能家庭

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This paper presents TRICA, a security framework for smart homes. When using controlling apps (e.g., smartphone app), TRICA makes sure that only legitimate users are allowed to control their Internet of Things (IoT) devices. Leveraging User Behavior Analytics (UBA) and Anomaly Detection (AD) techniques, TRI CA collects and processes the historical cyber and physical activities of the user in addition to the historical states of the smart home system to build a One Class Support Vector Machines (OCSVM) model. This model is then used as a baseline from which anomalous commands (i.e., outliers) should be detected and rejected, while normal commands (i.e., targets) should be considered as legitimate and allowed to be executed. Experiments conducted on adapted real-world data properly show the feasibility of such user behavior-based authentication approach. TRICA exhibits low false accept and false reject rates ensuring both security and user convenience, respectively.
机译:本文展示了Trica,智能家居安全框架。当使用控制应用程序(例如,智能手机应用程序)时,Trica确保允许仅允许合法的用户来控制其内容物(IoT)设备。利用用户行为分析(UBA)和异常检测(AD)技术,除了智能家居系统的历史状态外,TRI CA还收集和处理用户的历史网络和体力活动,以构建一类支持向量机(OCSVM ) 模型。然后将该模型用作基线,从该基线,应该检测和拒绝异常命令(即异常值),而正常命令(即目标)应被视为合法并允许执行。在适应的真实数据上进行的实验适当地显示了基于用户行为的身份验证方法的可行性。 Trica分别表现出低假的接受和虚假拒绝率,确保安全性和用户的便利性。

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