Toward a monitoring and threat detection system based on stream processing as a virtual network function for big data-Reference-Cited by-同舟云学术

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Toward a monitoring and threat detection system based on stream processing as a virtual network function for big data

Published:2019-05-21 Issue:20 Volume:31 Page:
ISSN:1532-0626
Container-title:Concurrency and Computation: Practice and Experience
language:en
Short-container-title:Concurrency Computat Pract Exper

Author:

Andreoni Lopez Martin¹²^ORCID,Mattos Diogo M. F.¹³,Duarte Otto Carlos M. B.¹,Pujolle Guy²

Affiliation:

1. Universidade Federal do Rio de Janeiro ‐ GTA/COPPE/UFRJ Rio de Janeiro Brazil

2. Sorbonne Université, CNRSLaboratoire d'Informatique de Paris 6 Paris France

3. Universidade Federal Fluminense ‐ TET/PPGEET/UFF Niterói Brazil

Funder

Conselho Nacional de Desenvolvimento Científico e Tecnológico

Coordenação de Aperfeiçoamento de Pessoal de Nível Superior

Fundação Carlos Chagas Filho de Amparo à Pesquisa do Estado do Rio de Janeiro

Fundação de Amparo à Pesquisa do Estado de São Paulo

Publisher

Wiley

Subject

Computational Theory and Mathematics,Computer Networks and Communications,Computer Science Applications,Theoretical Computer Science,Software

Link

https://onlinelibrary.wiley.com/doi/pdf/10.1002/cpe.5344

Reference33 articles.

1. BärA FinamoreA CasasP GolabL MelliaM.Large‐scale network traffic monitoring with DBStream a system for rolling big data analysis. Paper presented at: IEEE International Conference on Big Data;2014;Washington DC.

2. HuP LiH FuH CanseverD MohapatraP.Dynamic defense strategy against advanced persistent threat with insiders. Paper presented at: 2015 IEEE Conference on Computer Communications (INFOCOM) IEEE;2015;Kowloon Hong Kong.

3. Verizon Enterprise.Data Breach Investigations Report.www.verizonenterprise.com/resources/reports/rp_DBIR_2016_Report_en_xg.pdf.2016.

4. WuK ZhangK FanW EdwardsA YuPS.RS‐forest: a rapid density estimator for streaming anomaly detection. Paper presented at: IEEE International Conference on Data Mining (ICDM);2014;Shenzhen China.

5. MayhewM AtighetchiM AdlerA GreenstadtR.Use of machine learning in big data analytics for insider threat detection. Paper presented at: IEEE Military Communications Conference (MILCOM);2015;Tampa FL.

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