Abstract
Benchmarking is an essential tool for industrial organizations to identify potentials that allows them to improve their competitive position through operational and strategic means. However, the handling of sensitive information, in terms of (i) internal company data and (ii) the underlying algorithm to compute the benchmark, demands strict (technical) confidentiality guarantees—an aspect that existing approaches fail to address adequately. Still, advances in private computing provide us with building blocks to reliably secure even complex computations and their inputs, as present in industry benchmarks. In this paper, we thus compare two promising and fundamentally different concepts (hardware- and software-based) to realize privacy-preserving benchmarks. Thereby, we provide detailed insights into the concept-specific benefits. Our evaluation of two real-world use cases from different industries underlines that realizing and deploying secure information systems for industry benchmarking is possible with today’s building blocks from private computing.
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Notes
- 1.
We open-sourced them at https://github.com/COMSYS/industry-benchmarking.
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Acknowledgments
Funded by the Deutsche Forschungsgemeinschaft (DFG, German Research Foundation) under Germany’s Excellence Strategy – EXC-2023 Internet of Production – 390621612. We thank Jan-Gustav Michnia for his initial exploration of the FHE library CONCRETE [8]. We followed an abstract research methodology [21] to structure and organize our research collaborations.
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Pennekamp, J. et al. (2023). Designing Secure and Privacy-Preserving Information Systems for Industry Benchmarking. In: Indulska, M., Reinhartz-Berger, I., Cetina, C., Pastor, O. (eds) Advanced Information Systems Engineering. CAiSE 2023. Lecture Notes in Computer Science, vol 13901. Springer, Cham. https://doi.org/10.1007/978-3-031-34560-9_29
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