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@inproceedings{Evangelou:2016:10.1109/ISI.2016.7745445,
author = {Evangelou, M and Adams, N},
doi = {10.1109/ISI.2016.7745445},
publisher = {IEEE},
title = {Predictability of NetFlow data},
url = {http://dx.doi.org/10.1109/ISI.2016.7745445},
year = {2016}
}

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TY  - CPAPER
AB  - The behaviour of individual devices connected to anenterprise network can vary dramatically, as a device’s activitydepends on the user operating the device as well as on all behindthe scenes operations between the device and the network. Beingable to understand and predict a device’s behaviour in a networkcan work as the foundation of an anomaly detection framework,as devices may show abnormal activity as part of a cyber attack.The aim of this work is the construction of a predictive regressionmodel for a device’s behaviour at normal state. The behaviourof a device is presented by a quantitative response and modelledto depend on historic data recorded by NetFlow.
AU  - Evangelou,M
AU  - Adams,N
DO  - 10.1109/ISI.2016.7745445
PB  - IEEE
PY  - 2016///
TI  - Predictability of NetFlow data
UR  - http://dx.doi.org/10.1109/ISI.2016.7745445
UR  - http://hdl.handle.net/10044/1/39984
ER  -

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