Earticle

초록

영어

The Internet of Things has become a new sensing paradigm for interacting with the physical world. As the sensors in the Internet of Things are often deployed in harsh environments, this makes the sensors prone to failure and malfunctions, producing abnormal and erroneous data, known as outliers. Anomaly detection is critical in the Internet of Things to ensure the quality of data collected by sensors by detecting a high probability of incorrect reads or data corruption. Because the energy of sensor nodes in wireless sensor networks is limited, the transmission between nodes in centralized anomaly detection will consume a lot of energy. Therefore, we propose a distributed anomaly detection method based on a mixture of low precision and high precision to save node energy and improve network life.

목차

Abstract
I. INTRODUCTION
II. PROBLEM DESCRIPTION
III. THE DISTRIBUTED ANOMALY DETECTION
A. Low precision and low cost anomaly detection
B. High-precision anomaly detection (isolated forest)
C. Comprehensive anomaly score
D. Data exchange and weighted judgment of neighbor data
IV. CONCLUSION
REFERENCES

저자

• Qi Qiao [ School of Computer and Communication Engineering Changsha University of Science and Technology Changsha, China ]
• Shiming He [ School of Computer and Communication Engineering Changsha University of Science and Technology Changsha, China ]
• Bo Yang [ School of Computer and Communication Engineering Changsha University of Science and Technology Changsha, China ]

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