arXiv:2607. 15799v1 Announce Type: cross Abstract: Industrial processes often generate complex, interdependent time-series data from multiple sensors across multiple stages, forming complex dependencies among variables and process stages.
By Jaeyeong Lee, Taeseong Yoon, Wonmo Koo, Heeyoung Kim
arXiv:2606. 01691v1 Announce Type: cross Abstract: Industrial Internet systems face increasing threats from sophisticated industrial control system (ICS) attacks, resulting in critical safety incidents.
By Yuchen Zhang, Ning Xi, Pengbin Feng, Shigang Liu, Jianfeng Ma, Yulong Shen, Yanan Sun, Xiaolin Zhou
arXiv:2609.15483v1 Announce Type: new
Abstract: Unsupervised multivariate time series anomaly detection methods typically identify anomalies through forecasting, reconstruction, or representation dis...
By Zepeng Zhang, Fuad Khuri, Keivan Faghih Niresi, Olga Fink
arXiv:2603. 10676v2 Announce Type: replace Abstract: Industrial Control Systems (ICS) underpin critical infrastructure and face growing cyber-physical threats due to the convergence of operational technology and networked environments.
By Kosti Koistinen, Kirsi Hellsten, Joni Herttuainen, Kimmo K. Kaski
arXiv:2510. 26307v3 Announce Type: replace-cross Abstract: Anomaly detection is a critical task in cybersecurity, where identifying insider threats, access violations, and coordinated attacks is essential for ensuring system resilience.
By Laura Jiang, Reza Ryan, Qian Li, Nasim Ferdosian
arXiv:2608. 09246v1 Announce Type: new Abstract: Industrial processes are complex systems composed of multiple interacting sensors that generate multivariate time series (MTS).
By Sena Ozgunay (IMT, ANITI, LAAS-DISCO, LAAS, Comue de Toulouse), Louise Trav\'e-Massuy\`es (LAAS-DISCO, Comue de Toulouse, ANITI), Jean-Michel Loubes (IMT, REGALIA), Raul Sena Ferreira (LAAS)