Secure Computer Network: Strategies and Challengers in Big Data Era
| Autor: | Mercedes Barrionuevo, Mariela Lopresti, Natalia Miranda, Fabiana Piccoli |
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| Jazyk: | angličtina |
| Rok vydání: | 2018 |
| Předmět: | |
| Zdroj: | Journal of Computer Science and Technology, Vol 18, Iss 03, Pp e28-e28 (2018) |
| Druh dokumentu: | article |
| ISSN: | 1666-6046 1666-6038 16666038 |
| DOI: | 10.24215/16666038.18.e28 |
| Popis: | 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. |
| Databáze: | Directory of Open Access Journals |
| Externí odkaz: |
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