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Investigating the Impact of Cyber-Attack on Load Profile of Home Energy Management System
Anuebunwa, U Rajamani, HS Pillai, P Okpako, O
Anuebunwa, U
Rajamani, HS
Pillai, P
Okpako, O
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2018-01-01
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Abstract
© 2018, ICST Institute for Computer Sciences, Social Informatics and Telecommunications Engineering. Load profile for a household is key to understanding and applying automated load scheduling executed by the Home Energy Management Systems (HEMS). The provision of securing this basic domestic information as well as preventing intruders from being able to accessing and modifying them should be a matter of high priority. Any malicious attack on this data will have serious impact on the performance of the load scheduling algorithms. This paper is an investigation of how the scheduled load profile of a household can be deformed due to false data injection on the original load profile as a result of cyber-attack on the HEMS. Various incremental false data levels are introduced during an optimization process and the corresponding effect on the overall scheduled load profile is evaluated to understand the actual impact of the cyber-attack. Results show that as noise attack level increases, the optimized load profile shrinks and approaches a straight line which is equivalent to the average value of the original load profile. The implication of having such a load profile as a schedule is the obvious excessive disruption of a household’s energy use which results to having appliances switched ON or OFF at highly undesired times of the day thereby exacerbating user inconvenience.
Citation
Anuebunwa U., Rajamani HS., Pillai P., Okpako O. (2018) Investigating the Impact of Cyber-Attack on Load Profile of Home Energy Management System. In: Pillai P., Sithamparanathan K., Giambene G., Vázquez M., Mitchell P. (eds) Wireless and Satellite Systems. WiSATS 2017. Lecture Notes of the Institute for Computer Sciences, Social Informatics and Telecommunications Engineering, vol 231. Springer, Cham
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en
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1867-8211
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1867-822X
ISBN
9783319765709
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This work was supported by the British Council and the UK Department of Business Innovation and Skills under GII funding for the SITARA project.