Schep, Pim (2024) Privacy Analysis of Cloud-Based MPC. Integration Project, Industrial Engineering and Management.
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Abstract
This integration project explores the viability of outsourcing model predictive con- trol (MPC) to cloud-based services, focusing on privacy risks and mitigation strategies. The study specifically examines a quadruple-tank system (QTS), a complex, multivari- able physical process that poses significant challenges for real-time control systems. By shifting the computational demands of MPC to the cloud, the research aims to harness the extensive computational power available, while addressing the pivotal concern of data confidentiality. The QTS and the MPC are simulated in a MATLAB environment. This study places significant emphasis on the inference of key matrices which are pivotal to the MPC framework applied to the quadruple-tank system. The conclusion indicates that by outsourcing the computations of the MPC to the cloud, it is possible to derive certain critical matrices from the data known by the cloud, which represent the physical system and user preferences. Thereafter, two main cryptographic solutions, namely differential privacy and homomorphic encryption, are investigated for their efficacy in ensuring data privacy during cloud computation. Differential privacy is added to the system to prevent this matrix inference. The report outlines the conceptual design and problem statement, conducts a stakeholder analysis, and presents a comprehensive research framework leading to a detailed discussion of potential risks, encryption methodologies, and their practical implementation.
| Item Type: | Thesis (Integration Project) |
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| Supervisor name: | Monshizadeh Naini, N. and Hubl, A. and Hosseinalizadeh, T. |
| Degree programme: | Industrial Engineering and Management |
| Thesis type: | Integration Project |
| Language: | English |
| Date Deposited: | 02 Feb 2024 08:23 |
| Last Modified: | 02 Feb 2024 08:23 |
| URI: | https://fse.studenttheses.ub.rug.nl/id/eprint/31891 |
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