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(Reference retrieved automatically from Web of Science through information on FAPESP grant and its corresponding number as mentioned in the publication by the authors.)

Intelligent Network Security Monitoring Based on Optimum-Path Forest Clustering

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Author(s):
Guimaraes, Raniere Rocha [1] ; Passos Jr, Leandro A. ; Holanda Filho, Raimir [1] ; de Albuquerque, Victor Hugo C. [1] ; Rodrigues, Joel J. P. C. [2, 3] ; Komarov, Mikhail M. [4] ; Papa, Joao Paulo [5]
Total Authors: 7
Affiliation:
[1] Univ Fortaleza, Fortaleza, Ceara - Brazil
[2] Natl Inst Telecommun Inatel, Lisbon - Portugal
[3] Inst Telecomunicacoes, Lisbon - Portugal
[4] Natl Res Univ Higher Sch Econ, Dept Innovat & Business IT, Sch Business Informat, Fac Business & Management, Moscow - Russia
[5] Sao Paulo State Univ, Comp Sci Dept, Sao Paulo - Brazil
Total Affiliations: 5
Document type: Journal article
Source: IEEE NETWORK; v. 33, n. 2, p. 126-131, MAR-APR 2019.
Web of Science Citations: 2
Abstract

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. (AU)

FAPESP's process: 13/07375-0 - CeMEAI - Center for Mathematical Sciences Applied to Industry
Grantee:Francisco Louzada Neto
Support Opportunities: Research Grants - Research, Innovation and Dissemination Centers - RIDC
FAPESP's process: 14/16250-9 - On the parameter optimization in machine learning techniques: advances and paradigms
Grantee:João Paulo Papa
Support Opportunities: Regular Research Grants
FAPESP's process: 14/12236-1 - AnImaLS: Annotation of Images in Large Scale: what can machines and specialists learn from interaction?
Grantee:Alexandre Xavier Falcão
Support Opportunities: Research Projects - Thematic Grants
FAPESP's process: 16/19403-6 - Energy-based learning models and their applications
Grantee:João Paulo Papa
Support Opportunities: Regular Research Grants