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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.)

A threat monitoring system for intelligent data analytics of network traffic

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Guimaraes, Lucas C. B. [1] ; Rebello, Gabriel Antonio F. [1] ; Camilo, Gustavo F. [1] ; de Souza, Lucas Airam C. [1] ; Duarte, Otto Carlos M. B. [1]
Total Authors: 5
[1] Univ Fed Rio de Janeiro, Grp Teleinformat & Automacao, Rio De Janeiro - Brazil
Total Affiliations: 1
Document type: Journal article
Web of Science Citations: 0

Security attacks have been increasingly common and cause great harm to people and organizations. Late detection of such attacks increases the possibility of irreparable damage, with high financial losses being a common occurrence. This article proposes TeMIA-NT (ThrEat Monitoring and Intelligent data Analytics of Network Traffic), a real-time flow analysis system that uses parallel flow processing. The main contributions of the TeMIA-NT are (i) the proposal of an architecture for real-time detection of network intrusions that supports high traffic rates, (ii) the use of the structured streaming library, and (iii) two modes of operation: offline and online. The offline operation mode allows evaluating the performance of multiple machine learning algorithms over a given dataset, including metrics such as accuracy and F1-score. The proposed system uses dataframes and the structured streaming engine in online mode, which allows detection of threats in real-time and a quick reaction to attacks. To prevent or minimize the damage caused by security attacks, TeMIA-NT achieves flow-processing rates that reach 50 GB/s. (AU)

FAPESP's process: 15/24485-9 - Future internet for smart cities
Grantee:Fabio Kon
Support type: Research Projects - Thematic Grants
FAPESP's process: 14/50937-1 - INCT 2014: on the Internet of the Future
Grantee:Fabio Kon
Support type: Research Projects - Thematic Grants
FAPESP's process: 18/23292-0 - ACCRUE-SFI project: advanced collaborative research infrastructure for secure future internet
Grantee:Otto Carlos Muniz Bandeira Duarte
Support type: Regular Research Grants