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

키워드

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 ]

참고문헌

발행기관

간행물

표지보기 관심저널 등록

• 간행물명

  한국차세대컴퓨팅학회 학술대회

• 간기

  반년간

• 수록기간

  2021~2025

• 십진분류

  KDC 566 DDC 004