Secure Computer Network: Strategies and Challengers in Big Data Era
As computer networks have transformed in essential tools, their security has become a crucial problem for computer systems. Detecting unusual values from large volumes of information produced by network traffic has acquired huge interest in the network security area. Anomaly detection is a starting...
Main Authors: | , , , |
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Format: | Article |
Language: | English |
Published: |
Postgraduate Office, School of Computer Science, Universidad Nacional de La Plata
2018-12-01
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Series: | Journal of Computer Science and Technology |
Subjects: | |
Online Access: | http://journal.info.unlp.edu.ar/JCST/article/view/1116 |
Summary: | As computer networks have transformed in essential tools, their security has become a crucial problem for computer systems. Detecting unusual values from
large volumes of information produced by network traffic has acquired huge interest in the network security area. Anomaly detection is a starting point to
prevent attacks, therefore it is important for all computer systems in a network have a system of detecting anomalous events in a time near their occurrence. Detecting these events can lead network administrators to identify system failures, take preventive actions and avoid a massive damage.
This work presents, first, how identify network traffic anomalies through applying parallel computing techniques and Graphical Processing Units in two algorithms, one of them a supervised classification algorithm and the other based in traffic image processing.
Finally, it is proposed as a challenge to resolve the anomalies detection using an unsupervised algorithm as Deep Learning. |
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ISSN: | 1666-6046 1666-6038 |