SAFEM: Scalable analysis of flows with entropic measures and SVMReportar como inadecuado




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1 SnT - Interdisciplinary Centre for Security Relaibility and Trust 2 Uni.lu - Université du Luxembourg

Abstract : This paper describes a new approach for the detection of large-scale anomalies or malicious events in Netflow records. This approach allows Internet operators, to whom botnets and spam are major threats, to detect large-scale distributed attacks. The prototype SAFEM Scalable Analysis of Flows with Entropic Measures uses spatial-temporal Netflow record aggregation and applies entropic measures to traffic. The aggregation scheme highly reduces data storage leading to the viability of using such an approach in an Internet Service Provider network.

Keywords : Flows Support Vector Machines Anomaly





Autor: Jérôme François - Cynthia Wagner - Radu State - Thomas Engel -

Fuente: https://hal.archives-ouvertes.fr/



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