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Intrusion Detection System

Table of contents

Failure Detection

  1. A Systematic Survey on Sensor Failure Detection and Fault-Tolerance in Ambient Assisted Living [Sensor, 2018]

  2. Failuresense: Detecting sensor failure using electrical appliances in the home [MASS, 2014]

  3. Using temporal correlation and time series to detect missing activity-driven sensor events [PERCOM, 2015]

  4. Idea: A system for efficient failure management in smart iot environments [Mobisys, 2016]

  5. Data reconciliation in a smart home sensor network [Expert Systems with Applications, 2013 ]

  6. Detecting abnormal events on binary sensors in smart home environments [Pervasive and Mobile Computing, 2016]

  7. Fault detection for binary sensors in smart home environments [PERCOM, 2015]

  8. Being SMART about failures: Assessing repairs in SMART homes [Ubicomp,2012]

  9. A fault detection and diagnosis framework for ambient intelligent systems [Autonomic and Trusted Computing, 2012]

  10. Generating Bayesian Network Structures for Self-diagnosis of Sensor Networks in the Context of Ambient Assisted Living for Aging Well [Smart Homes and Health Telematics, 2017]

  11. Fall-curve: A novel primitive for IoT Fault Detection and Isolation [Sensys, 2018]

  12. Detecting Anomalous Sensor Events in Smart Home Data for Enhancing the Living Experience [AAAI, 2011]

  13. Towards Sensor Failure Detection in Ambient Assisted Living: Sensors Correlations [CASE, 2018]

  14. Sensor network data fault types [TOSN, 2009]

  15. Anomaly detection in wireless sensor networks in a nonstationary environment [Communications Surveys & Tutorials, 2014]

  16. Sensor faults: Detection methods and prevalence in real-world datasets [TOSN, 2010]

  17. Online outlier detection in sensor data using non-parametric models [VLDB, 2006]

  18. Distributed online outlier detection in wireless sensor networks using ellipsoidal support vector machine [Ad hoc networks, 2013]

Smart Environment Prediction

  1. Survey on Prediction Algorithms in Smart Homes [IoTJ, 2018]

  2. Using Temporal Relations in Smart Environment Data for Activity Prediction [ICML 2007]

  3. Prediction of the Next Sensor Event and Its Time of Occurrence in Smart Homes [ICNAA 2019]

Activities of Daily Living

  1. Unsupervised Recognition of Interleaved Activities of Daily Living through Ontological and Probabilistic Reasoning [Ubicomp, 2016]

  2. SmartFABER: Recognizing Fine-grained Abnormal Behaviors for Early Detection of Mild Cognitive Impairment [Artificial intelligence in medicine, 2016]

  3. Reasoning with smart objects’ affordance for personalized behavior monitoring in pervasive information systems [Knowledge and Information Systems, 2019]

  4. Demultiplexing Activities of Daily Living in IoT enabled Smarthomes [Inforcom, 2016]

  5. Activity and Anomaly Detection in Smart Home: A Survey [Next Generation Sensors and Systems, 2016]

  6. Anomaly Detection Models for Smart Home Security [BigDataSecurity, 2019]

  7. A Probabilistic Ontological Framework for the Recognition of Multilevel Human Activities [Pervasive and ubiquitous computing, 2013]

Event Spoofing Detection

  1. Peeves: Physical Event Verification in Smart Homes [CCS, 2019]

Anomaly Detection Survey

  1. Deep learning for anomaly detection: A survey [arxiv, 2019]