A Novel Probabilistic Hybrid Model to Detect Anomaly in Smart Homes

作     者：Sasan Saqaeeyan Hamid Haj Seyyed Javadi Hossein Amirkhani 

作者机构：Department of Computer EngineeringBorujerd BranchIslamic Azad UniversityBorujerdIran Department of Mathematics and Computer ScienceShahed UniversityTehranIran Computer Engineering and Information Technology DepartmentUniversity of QomQomIran 

出 版 物：《Computer Modeling in Engineering & Sciences》 (工程与科学中的计算机建模（英文）)

年 卷 期：2019年第121卷第12期

页      面：815-834页

核心收录：

学科分类：08[工学] 0835[工学-软件工程] 0811[工学-控制科学与工程] 0701[理学-数学] 0812[工学-计算机科学与技术（可授工学、理学学位）] 

主　　题：Smart homes sensory data anomaly detection Bayesian networks ensemble method 

摘      要：Anomaly detection in smart homes provides support to enhance the health and safety of people who live *** to the previous studies done on this topic,less attention has been given to hybrid *** paper presents a two-steps hybrid probabilistic anomaly detection model in the smart ***,it employs various algorithms with different characteristics to detect anomalies from sensory ***,it aggregates their results using a Bayesian *** this Bayesian network,abnormal events are detected through calculating the probability of abnormality given anomaly detection results of base *** evaluation of a real dataset indicates the effectiveness of the proposed method by reducing false positives and increasing true positives.