Intelligent Network Security Monitoring Based on Optimum-Path Forest Clustering - Guimaraes, Raniere Rocha; Passos Jr, Leandro A.; Holanda Filho, Raimir; Albuquerque, Victor Hugo C. de; Rodrigues, Joel J. P. C.; Komarov, Mikhail M.; Papa, Joao Paulo [UNESP] (Ieee-inst Electrical Electronics Engineers Inc, 2019)
Distinguishing outliers from normal data in wireless sensor networks has been a big challenge in the anomaly detection domain, mostly due to the nature of the anomalies, such as software or hardware failures, reading errors or malicious attacks, just to name a few. In this article, we introduce an anomaly detection-based OPF classifier in the aforementioned context. The results are compared against one-class support vector machines and multivariate Gaussian distribution. Additionally, we also propose to employ meta-heuristic optimization techniques to fine-tune the OPF classifier in the context of anomaly detection in wireless sensor networks.