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Bi-level poisoning attack model and countermeasure for appliance consumption data of smart homes

Billah, M, Anwar, Adnan, Rahman, Z and Galib, SM 2021, Bi-level poisoning attack model and countermeasure for appliance consumption data of smart homes, Energies, vol. 14, no. 13, pp. 1-17, doi: 10.3390/en14133887.

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Title Bi-level poisoning attack model and countermeasure for appliance consumption data of smart homes
Author(s) Billah, M
Anwar, AdnanORCID iD for Anwar, Adnan orcid.org/0000-0003-3916-1381
Rahman, Z
Galib, SM
Journal name Energies
Volume number 14
Issue number 13
Article ID 3887
Start page 1
End page 17
Total pages 17
Publisher MDPI
Place of publication Basel, Switzerland
Publication date 2021-07-01
ISSN 1996-1073
Keyword(s) DEMAND
DETERMINANTS
ELECTRICITY CONSUMPTION
Energy & Fuels
energy usage
ENERGY-CONSUMPTION
home appliances
poisoning attack
prediction model
regression
Science & Technology
Technology
Summary Accurate building energy prediction is useful in various applications starting from building energy automation and management to optimal storage control. However, vulnerabilities should be considered when designing building energy prediction models, as intelligent attackers can deliberately influence the model performance using sophisticated attack models. These may consequently degrade the prediction accuracy, which may affect the efficiency and performance of the building energy management systems. In this paper, we investigate the impact of bi-level poisoning attacks on regression models of energy usage obtained from household appliances. Furthermore, an effective countermeasure against the poisoning attacks on the prediction model is proposed in this paper. Attacks and defenses are evaluated on a benchmark dataset. Experimental results show that an intelligent cyber-attacker can poison the prediction model to manipulate the decision. However, our proposed solution successfully ensures defense against such poisoning attacks effectively compared to other benchmark techniques.
Language eng
DOI 10.3390/en14133887
Field of Research 02 Physical Sciences
09 Engineering
HERDC Research category C1 Refereed article in a scholarly journal
Free to Read? Yes
Persistent URL http://hdl.handle.net/10536/DRO/DU:30153298

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Every reasonable effort has been made to ensure that permission has been obtained for items included in DRO. If you believe that your rights have been infringed by this repository, please contact drosupport@deakin.edu.au.