Abstract
A Bloom filter, originally proposed by Bloom in 1970, is a probabilistic data structure used to determine membership in a set with enduring false positive errors. Due to the trade-off between space efficiency and the probability of false positive errors, Bloom filters have found numerous applications in network systems and various fields of information sciences. Chazelle et al. [6] extended this concept to a more versatile data structure known as the Bloomier filter, capable of encoding arbitrary functions. With Bloomier filters, it becomes possible to associate values with specific elements of the domain, enabling more generalized use. In this paper, we propose a variant of Charles and Chellapilla’s scheme [5] that utilizes minimal perfect hashings. Specifically, instead of using bipartite random graphs like existing Bloomier filters, we present a space-efficient Bloomier filter with faster creation time based on an analysis of 3-hypergraphs, in comparison to previous results.
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Acknowledgements
This research was in part conducted under a contract of “Research and development on new generation cryptography for secure wireless communication services” among “Research and Development for Expansion of Radio Wave Resources (JPJ000254)”, which was supported by the Ministry of Internal Affairs and Communications, Japan. This work was in part supported by JSPS KAKENHI Grant Number JP22K19773.
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Jo, H., Shikata, J. (2024). Bloomier Filters on 3-Hypergraphs. In: Kim, H., Youn, J. (eds) Information Security Applications. WISA 2023. Lecture Notes in Computer Science, vol 14402. Springer, Singapore. https://doi.org/10.1007/978-981-99-8024-6_2
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DOI: https://doi.org/10.1007/978-981-99-8024-6_2
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