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| Title: | Scenario based defense mechanism for distributed model predictive control | | | Authors: | P. Velarde, J.M. Maestre, H. Ishii, R.R. Negenborn |
| | Conference: | 56th IEEE Conference on Decision and Control (CDC2017) | | Address: | Melbourne, Australia | | Date: | December 2017 |
| | Abstract: | In this paper, we present an analysis of the vulnerability of a distributed model predictive control (DMPC) scheme in the context of cyber-security. We consider different types of the so-called insider attacks. In particular, we consider the situation where one of the local controllers sends false information to others to manipulate costs for its own advantage. Then, we propose a popular scenario-based mechanism to protect or, at least, relieve the consequences of the attack in a typical DMPC negotiation procedure. A realistic case study based on a local energy grid of households is provided to illustrate both the consequences of the attacks and the defense mechanisms. |
| | Reference: | Scenario based defense mechanism for distributed model predictive control. P. Velarde, J.M. Maestre, H. Ishii, R.R. Negenborn. In Proceedings of the 56th IEEE Conference on Decision and Control (CDC2017), Melbourne, Australia, pp. 6171-6176, December 2017. | | | Request: | A
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