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Gilberto Fernandes

Researcher at University of Beira Interior

Publications -  9
Citations -  338

Gilberto Fernandes is an academic researcher from University of Beira Interior. The author has contributed to research in topics: Network management & Anomaly detection. The author has an hindex of 6, co-authored 8 publications receiving 213 citations. Previous affiliations of Gilberto Fernandes include Universidade Estadual de Londrina.

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Journal ArticleDOI

A comprehensive survey on network anomaly detection

TL;DR: The main objective is to review the most important aspects pertaining to anomaly detection, covering an overview of a background analysis as well as a core study on the most relevant techniques, methods, and systems within the area.
Journal ArticleDOI

Network anomaly detection using IP flows with Principal Component Analysis and Ant Colony Optimization

TL;DR: Two novel anomaly detection mechanisms based on statistical procedure Principal Component Analysis and the Ant Colony Optimization metaheuristic are presented and compared, demonstrating that the systems are able to enhance the detection of anomalous behavior by maintaining a satisfactory false-alarm rate.
Journal ArticleDOI

Autonomous profile-based anomaly detection system using principal component analysis and flow analysis

TL;DR: An autonomous anomaly detection system based on the statistical method principal component analysis (PCA) that creates a network profile called Digital Signature of Network Segment using Flow Analysis (DSNSF) that denotes the predicted normal behavior of a network traffic activity through historical data analysis.
Journal ArticleDOI

Digital signature of network segment for healthcare environments support

TL;DR: Digital Signature of Network Segment using Flow analysis (DSNSF) as a mechanism to assist the networks management through traffic characterization is introduced and an approach for anomaly detection is proposed, which is able to recognize unusual events that may affect the proper operation of the services provided by the network.
Proceedings ArticleDOI

A novel anomaly detection system to assist network management in SDN environment

TL;DR: This paper presents a system designed to proactively monitor network traffic and autonomously detect anomalies which may impair the proper network functioning and provides routines that allow the mitigation of the anomalies effects.