Privacy Preserving Queries of Shortest Path Distances
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Publisher
Springer International Publishing
Link
https://link.springer.com/content/pdf/10.1007/978-3-031-33437-5_6
Reference16 articles.
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3. Akavia, A., Leibovich, M., Resheff, Y.S., Ron, R., Shahar, M., Vald, M.: Privacy-preserving decision trees training and prediction. IACR Cryptol. ePrint Arch. 768 (2021). https://eprint.iacr.org/2021/768
4. Anagreh, M., Laud, P., Vainikko, E.: Privacy-preserving parallel computation of shortest path algorithms with low round complexity. In: Mori, P., Lenzini, G., Furnell, S. (eds.) Proceedings of the 8th International Conference on Information Systems Security and Privacy, ICISSP 2022, Online Streaming, February 9–11, 2022, pp. 37–47. SCITEPRESS (2022). https://doi.org/10.5220/0010775700003120
5. Bahrdt, D., Funke, S., Makolli, S., Proissl, C.: Distance closures: unifying search- and lookup-based shortest path speedup techniques. In: Phillips, C.A., Speckmann, B. (eds.) Proceedings of the Symposium on Algorithm Engineering and Experiments, ALENEX 2022, Alexandria, VA, USA, 9–10 January 2022, pp. 1–12. SIAM (2022). https://doi.org/10.1137/1.9781611977042.1
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