An Interpretable Multivariate Time-Series Anomaly Detection Method in Cyber–Physical Systems Based on Adaptive Mask-Reference-Cited by-同舟云学术

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An Interpretable Multivariate Time-Series Anomaly Detection Method in Cyber–Physical Systems Based on Adaptive Mask

Published:2024-01-15 Issue:2 Volume:11 Page:2728-2740
ISSN:2327-4662
Container-title:IEEE Internet of Things Journal
language:
Short-container-title:IEEE Internet Things J.

Author:

Zhu Haiqi¹^ORCID,Yi Chunzhi²^ORCID,Rho Seungmin³^ORCID,Liu Shaohui¹^ORCID,Jiang Feng¹^ORCID

Affiliation:

1. Department of Computer Science and Technology, Harbin Institute of Technology, Harbin, China

2. Department of Medicine and Health, Harbin Institute of Technology, Harbin, China

3. Department of Industrial Security, Chung-Ang University, Seoul, South Korea

Funder

National Natural Science Foundation of China

Natural Science Foundation of Chongqing

Postdoctoral Science Foundation of Heilongjiang Province of China

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Computer Networks and Communications,Computer Science Applications,Hardware and Architecture,Information Systems,Signal Processing

Link

http://xplorestaging.ieee.org/ielx7/6488907/10384482/10177932.pdf?arnumber=10177932

Reference61 articles.

1. Intelligent Detection for Key Performance Indicators in Industrial-Based Cyber-Physical Systems

2. Anomaly secure detection methods by analyzing dynamic characteristics of the network traffic in cloud communications

3. Two Birds with One Stone: Series Saliency for Accurate and Interpretable Multivariate Time Series Forecasting

4. Intelligible Models for HealthCare

5. The Mythos of Model Interpretability

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1. Multivariate time series anomaly detection: Missing data handling and feature collaborative analysis in robot joint data;Journal of Manufacturing Systems;2024-08

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