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A Framework for Learning Event Sequences and Explaining Detected Anomalies in a Smart Home Environment.

Justin Baudisch1, Birte Richter2, Thorsten Jungeblut1

  • 1Faculty of Engineering and Mathematics, Bielefeld University of Applied Sciences, Bielefeld, Germany.

Kunstliche Intelligenz
|November 7, 2022
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Summary

This study introduces a smart home anomaly detection framework using event sequences to learn user behavior. It identifies deviations from normal patterns and explains anomalies through rule analysis.

Keywords:
Ambient assisted livingAnomaly detectionExplainable AIInternet of things

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Area of Science:

  • Artificial Intelligence
  • Smart Home Technology
  • Cybersecurity

Background:

  • Smart home systems generate vast amounts of data from Internet of Things (IoT) devices.
  • Detecting anomalies in user behavior is crucial for security and system optimization.
  • Existing methods often lack explainability for detected anomalies.

Purpose of the Study:

  • To develop a framework for learning event sequences for anomaly detection in smart homes.
  • To enhance the explainability of detected anomalies.
  • To model and identify deviations from habitual user behavior.

Main Methods:

  • Modeling user behavior as event sequences from IoT device interactions.
  • Learning habitual behavior from recorded event sequences.
  • Implementing anomaly detection as deviations from learned normal behavior.
  • Utilizing simple rule analysis for anomaly explainability.

Main Results:

  • A framework capable of learning user behavior patterns from smart home event data.
  • Successful identification of anomalies as deviations from learned habitual behavior.
  • Demonstrated explainability of detected anomalies through rule analysis.

Conclusions:

  • The proposed framework effectively detects anomalies in smart home environments by learning event sequences.
  • Explainability of anomalies is achieved, providing insights into deviations from normal user behavior.
  • The method offers a robust approach for enhancing smart home security and performance.