title: Activity Learning as a Foundation for Security Monitoring in Smart Homes.
abstract: Smart environment technology has matured to the point where it is regularly used in everyday homes as well as research labs. With this maturation of the technology, we can consider using smart homes as a practical mechanism for improving home security. In this paper, we introduce an activity-aware approach to security monitoring and threat detection in smart homes. We describe our approach using the CASAS smart home framework and activity learning algorithms. By monitoring for activity-based anomalies we can detect possible threats and take appropriate action. We evaluate our proposed method using data collected in CASAS smart homes and demonstrate the partnership between activity-aware smart homes and biometric devices in the context of the CASAS on-campus smart apartment testbed.
authors.affiliation: School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA. jb3dahmen@wsu.edu.
authors.forename: Jessamyn
authors.initials: J
authors.lastname: Dahmen
authors.affiliation: School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA. bthomas@eecs.wsu.edu.
authors.forename: Brian L
authors.initials: BL
authors.lastname: Thomas
authors.affiliation: School of Electrical Engineering and Computer Science, Washington State University, Pullman, WA 99164, USA. cook@eecs.wsu.edu.
authors.forename: Diane J
authors.initials: DJ
authors.lastname: Cook
authors.affiliation: FutureWei Technologies, Inc., Santa Clara, CA 95050, USA. xiaobo.sc.wang@huawei.com.
authors.forename: Xiaobo
authors.initials: X
authors.lastname: Wang
keywords: activity learning; anomaly detection; security monitoring; smart home automation