A Software Approach to Improving Cloud Computing Datacenter Energy Efficiency and Enhancing Security through Botnet Detection

Dinita, Razvan-Ioan and Winckles, Adrian and Wilson, George (2017) A Software Approach to Improving Cloud Computing Datacenter Energy Efficiency and Enhancing Security through Botnet Detection. In: 2016 IEEE 14th International Conference on Industrial Informatics (INDIN), 19-21 July 2016, Futuroscope-Poitiers, France.

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Official URL: http://dx.doi.org/10.1109/INDIN.2016.7819272


This work presents positive experiment results on the efficiency and security potential of an optimized and novel approach to an Autonomous Management Distributed System (AMDS) running in a Cloud Computing environment. The results validate the AMDS software design and demonstrate its potential as an industrial application to be used in modern datacenters. On one hand, from an operational performance point of view, they show the AMDS’ ability of reconfiguring itself on the fly, thus resulting in 14 percent increased efficiency over the lifetime of the first experiment. On the other hand, they show an overall malicious (Botnet) data packet detection rate of over 52 percent, a significant percentage for only 5000 network data samples analyzed by the Botnet software module plugged into the AMDS. Both experiments have been performed in a VMWare run cloud environment, however due to the AMDS’ abstract architecture, it has the potential to interface with any existing cloud management system that exposes an API.

Item Type: Conference or Workshop Item (Paper)
Additional Information: © 2017 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Keywords: Cloud Computing
Faculty: ARCHIVED Faculty of Science & Technology (until September 2018)
Depositing User: Ian Walker
Date Deposited: 20 Feb 2017 15:09
Last Modified: 09 Sep 2021 18:59
URI: https://arro.anglia.ac.uk/id/eprint/701526

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