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Detecting Advanced Network Threats Using a Similarity Search

  • Milan Čermák
  • Pavel Čeleda
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 9701)

Abstract

In this paper, we propose a novel approach for the detection of advanced network threats. We combine knowledge-based detections with similarity search techniques commonly utilized for automated image annotation. This unique combination could provide effective detection of common network anomalies together with their unknown variants. In addition, it offers a similar approach to network data analysis as a security analyst does. Our research is focused on understanding the similarity of anomalies in network traffic and their representation within complex behaviour patterns. This will lead to a proposal of a system for the real-time analysis of network data based on similarity. This goal should be achieved within a period of three years as a part of a PhD thesis.

Keywords

Similarity search Network data Classification Network threats 

Notes

Acknowledgement

This research was supported by the Security Research Programme of the Czech Republic 2015 - 2020 (BV III/1 VS) granted by the Ministry of the Interior of the Czech Republic under No. VI20162019029 The Sharing and analysis of security events in the Czech Republic.

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Copyright information

© IFIP International Federation for Information Processing 2016

Authors and Affiliations

  1. 1.Institute of Computer ScienceMasaryk UniversityBrnoCzech Republic

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