Mobile agent-based cross-layer anomaly detection in smart home sensor networks using fuzzy logic

Despite the rapid advancements in consumer electronics, the data transmitted by sensing devices in a smart home environment are still vulnerable to anomalies due to node faults, transmission errors, or attacks. This affects the reliability of the received sensed data and may lead to the incorrect de...

Full description

Saved in:
Bibliographic Details
Published in:IEEE transactions on consumer electronics 2015-05, Vol.61 (2), p.197-205
Main Authors: Usman, Muhammad, Muthukkumarasamy, Vallipuram, Xin-Wen Wu
Format: Article
Language:English
Subjects:
Anomaly Detection
Cross-Layer Design
Expert systems
Feature extraction
Fuzzy logic
Intelligent agents
Mobile Agent
Mobile agents
Mobile communication
Peer-to-peer computing
Smart Home Sensor Networks
Smart homes
Citations: Items that this one cites
Items that cite this one
Online Access:Get full text
Tags: Add Tag
No Tags, Be the first to tag this record!
Description
Summary:Despite the rapid advancements in consumer electronics, the data transmitted by sensing devices in a smart home environment are still vulnerable to anomalies due to node faults, transmission errors, or attacks. This affects the reliability of the received sensed data and may lead to the incorrect decision making at both local (i.e., smart home) and global (i.e., smart city) levels. This study introduces a novel mobile agent-based cross-layer anomaly detection scheme, which takes into account stochastic variability in cross-layer data obtained from received data packets, and defines fuzzy logic-based soft boundaries to characterize behavior of sensor nodes. This cross-layer design approach empowers the proposed scheme to detect both node and link anomalies, and also effectively transmits mobile agents by considering the communication link-state before transmission of the mobile agent. The proposed scheme is implemented on a real testbed and a modular application software is developed to manage the anomaly detection system in the smart home. The experimental results show that the proposed scheme detects cross-layer anomalies with high accuracy and considerably reduces the energy consumption caused by the mobile agent transmission in the poor communication link-state situations.
ISSN:0098-3063
1558-4127
DOI:10.1109/TCE.2015.7150594