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Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
Research output: Contribution in Book/Report/Proceedings - With ISBN/ISSN › Conference contribution/Paper › peer-review
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TY - GEN
T1 - Adversarial Machine Learning in Smart Energy Systems
AU - Bor, Martin
AU - Marnerides, Angelos
AU - Molineux, Andy
AU - Wattam, Steve
AU - Roedig, Utz
N1 - Conference code: 10
PY - 2019/6/25
Y1 - 2019/6/25
N2 - Smart Energy Systems represent a radical shift in the approach to energy generation and demand, driven by decentralisation of the energy system to large numbers of low-capacity devices. Managing this flexibility is often driven by machine learning, and requires real-time control and aggregation of these devices, involving a diverse set of companies and devices and creating a longer chain of trust. This poses a security risk, as it is sensitive to adversarial machine learning, whereby models are fooled through malicious input, either for financial gain or to cause system disruption. We show the feasibility of such an attack by analysing empirical data of a real system, and propose directions for future research related to detection and defence mechanisms for these kind of attacks.
AB - Smart Energy Systems represent a radical shift in the approach to energy generation and demand, driven by decentralisation of the energy system to large numbers of low-capacity devices. Managing this flexibility is often driven by machine learning, and requires real-time control and aggregation of these devices, involving a diverse set of companies and devices and creating a longer chain of trust. This poses a security risk, as it is sensitive to adversarial machine learning, whereby models are fooled through malicious input, either for financial gain or to cause system disruption. We show the feasibility of such an attack by analysing empirical data of a real system, and propose directions for future research related to detection and defence mechanisms for these kind of attacks.
U2 - 10.1145/3307772.3330171
DO - 10.1145/3307772.3330171
M3 - Conference contribution/Paper
SP - 413
EP - 415
BT - e-Energy '19 Proceedings of the Tenth ACM International Conference on Future Energy Systems
PB - ACM
CY - New York
T2 - Tenth ACM International Conference on Future Energy Systems (ACM e-Energy)
Y2 - 25 June 2019 through 28 June 2019
ER -