An Anomaly Detection Method for Stateful Stream Processing System
Guanghui Chang, Lu Zhao, Jun Liu, Peizhen Li
Available Online March 2017.
- 10.2991/msam-17.2017.44How to use a DOI?
- stream processing; complex event processing; kpca; svm
The SSPS (stateful stream processing system) is a distributed complex event processing system implemented by the framework of stream processing system. However, due to the nature of uncertainty, randomness and burstiness of the data stream and the complexity of complex event processing, the SSPS faces great challenges. In order to address the problem, this paper analyzes the problems of SSPS, on this basis, an anomaly detection method based on FKPCA-SVM is proposed. Experimental results show that the proposed method can efficiently and reliably detect SSPS, and ensure the system can operate normally.
- © 2017, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Guanghui Chang AU - Lu Zhao AU - Jun Liu AU - Peizhen Li PY - 2017/03 DA - 2017/03 TI - An Anomaly Detection Method for Stateful Stream Processing System BT - Proceedings of the 2017 2nd International Conference on Modelling, Simulation and Applied Mathematics (MSAM2017) PB - Atlantis Press SP - 196 EP - 199 SN - 1951-6851 UR - https://doi.org/10.2991/msam-17.2017.44 DO - 10.2991/msam-17.2017.44 ID - Chang2017/03 ER -