Text-Mining Research Group

Assessment Simulation Model for Uncoupled Message Authentication

Today’s trend of an increasing number of networked embedded devices pervades many areas. Ranging from home automation, industrial or automotive applications with a large number of different protocols, low resources and often high demands on real-time make it difficult to secure the communication of such systems. A concept of an uncoupled MAC which is able to ensure the authenticity and integrity of communication flows between two network parties can be used. This is in particular of advance for outdated legacy components still participating in the network. In this paper a assessment simulation model of the mechanism behind this technology is described. It outlines the probability of detecting an attack depending on the message authentication overhead. The model considers all control variables and performs measurements based on random data traffic. The results of the statistical analysis state that a high attack detection rate can be obtained even with a small communication overhead.

This is a preprint version of the article.

Keywords: simulation; model; message authentication

Year: 2017

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Laurin Doerr

Dalibor Fiala

Phone: +420 377 63 2429
E-mail: dalfia@kiv.zcu.cz
WWW: http://www.kiv.zcu.cz/~dalfia/

Dalibor is the research group coordinator and an associate professor at the Department of Computer Science and Engineering at the University of West Bohemia in Pilsen, Czech Republic. He is interested in data mining, web mining, information retrieval, informetrics, and information science.

Michael Heigl

E-mail: heigl@kiv.zcu.cz

Michael is currently working as a research associate at the institute ProtectIT at the Deggendorf Institute of Technology and holds a Ph.D. degree from the University of West Bohemia for his dissertation on machine learning enhanced network-based anomaly detection. He is specialized in improving outlier detection methods for streaming data applications.

Martin Schramm

Data Mining for Computer Networks Security
Authors:	Michael Heigl, Laurin Doerr, Dalibor Fiala
Desc.:	Novel data mining methods for the enhancement of computer networks security using advanced outlier detection techniques on streaming data are investigated.