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Security and Communication Networks
Volume 2017, Article ID 9150965, 17 pages
Review Article

Towards Large-Scale, Heterogeneous Anomaly Detection Systems in Industrial Networks: A Survey of Current Trends

Department of Electronics and Computing, Mondragon Unibertsitatea, Goiru 2, 20500 Arrasate-Mondragón, Spain

Correspondence should be addressed to Mikel Iturbe; ude.nogardnom@ebrutim

Received 13 September 2017; Accepted 5 November 2017; Published 22 November 2017

Academic Editor: Javier Lopez

Copyright © 2017 Mikel Iturbe et al. This is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.

Citations to this Article [3 citations]

The following is the list of published articles that have cited the current article.

  • Javier Hingant, Marcelo Zambrano, Francisco J. Pérez, Israel Pérez, and Manuel Esteve, “HYBINT: A Hybrid Intelligence System for Critical Infrastructures Protection,” Security and Communication Networks, vol. 2018, pp. 1–13, 2018. View at Publisher · View at Google Scholar
  • Xiangyu Xi, Tong Zhang, Wei Ye, Zhao Wen, Shikun Zhang, Dongdong Du, and Qing Gao, “An Ensemble Approach for Detecting Anomalous User Behaviors,” International Journal of Software Engineering and Knowledge Engineering, vol. 28, no. 11n12, pp. 1637–1656, 2019. View at Publisher · View at Google Scholar
  • Li Ruan, Shupan Li, Rongbin Xu, Shubin Su, Limin Xiao, Fei Gu, and Zhaokai Wang, “An Efficient Density-Based Local Outlier Detection Approach for Scattered Data,” IEEE Access, vol. 7, pp. 1006–1020, 2019. View at Publisher · View at Google Scholar