A space-embedding strategy for anomaly detection in multivariate time series

Z Ji, Y Wang, K Yan, X Xie, Y Xiang, J Huang - Expert Systems with …, 2022 - Elsevier
Anomaly detection of time series has always been a hot topic in academia and industry.
However, many existing multivariant time series methods suffer from common challenges …

[HTML][HTML] Anomaly detection method for multivariate time series data of oil and gas stations based on digital twin and mtad-gan

Y Lian, Y Geng, T Tian - Applied Sciences, 2023 - mdpi.com
Due to the complexity of the oil and gas station system, the operational data, with various
temporal dependencies and inter-metric dependencies, has the characteristics of diverse …

A fast, decentralized covariance selection-based approach to detect cyber attacks in smart grids

R Moslemi, A Mesbahi, JM Velni - IEEE Transactions on Smart …, 2017 - ieeexplore.ieee.org
Recent studies have shown that an attacker can compromise some of the power grid
measurements to mislead the conventional state estimators (SEs), since the manipulated …

Change detection in dynamic attributed networks

IU Hewapathirana - Wiley Interdisciplinary Reviews: Data …, 2019 - Wiley Online Library
A network provides powerful means of representing complex relationships between entities
by abstracting entities as vertices, and relationships as edges connecting vertices in a …

Statistical structure learning to ensure data integrity in smart grid

H Sedghi, E Jonckheere - IEEE Transactions on Smart Grid, 2015 - ieeexplore.ieee.org
Robust control and management of the grid relies on accurate data. Both phasor
measurement units and remote terminal units are prone to false data injection attacks. Thus …

Detecting users' anomalous emotion using social media for business intelligence

X Sun, C Zhang, G Li, D Sun, F Ren, A Zomaya… - Journal of …, 2018 - Elsevier
Anomaly detection in sentiment analysis refers to detecting users' abnormal opinions,
sentiment patterns or special temporal aspects of such patterns. Users' emotional state …

Anomaly localization for network data streams with graph joint sparse PCA

R Jiang, H Fei, J Huan - Proceedings of the 17th ACM SIGKDD …, 2011 - dl.acm.org
Determining anomalies in data streams that are collected and transformed from various
types of networks has recently attracted significant research interest. Principal Component …

Multi-task multi-modal models for collective anomaly detection

T Idé, DT Phan, J Kalagnanam - 2017 IEEE International …, 2017 - ieeexplore.ieee.org
This paper proposes a new framework for anomaly detection when collectively monitoring
many complex systems. The prerequisite for condition-based monitoring in industrial …

CONGO²: Scalable Online Anomaly Detection and Localization in Power Electronics Networks

J Yu, H Cheng, J Zhang, Q Li, S Wu… - IEEE internet of …, 2022 - ieeexplore.ieee.org
Rapid and accurate detection and localization of electronic disturbances simultaneously are
important for preventing its potential damages and determining potential remedies. The …

Variable selection for kernel two-sample tests

J Wang, SS Dey, Y Xie - arXiv preprint arXiv:2302.07415, 2023 - arxiv.org
We consider the variable selection problem for two-sample tests, aiming to select the most
informative variables to distinguish samples from two groups. To solve this problem, we …