{"title":"On the False Positive Rate of the Bloom Filter in Case of Using Multiple Hash Functions","authors":"Jihong Kim","doi":"10.1109/AsiaJCIS.2014.32","DOIUrl":null,"url":null,"abstract":"A Bloom filter is a simple space-efficient randomized data structure used to represent set in order to support membership queries. So it is very useful to search the wanted data from the all entries. In this paper, we analyze the probability of the false positive rate of the Bloom filter used in various applications up to now and present the revised false positive rate of Bloom filter.","PeriodicalId":354543,"journal":{"name":"2014 Ninth Asia Joint Conference on Information Security","volume":"21 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2014-09-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"5","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"2014 Ninth Asia Joint Conference on Information Security","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.1109/AsiaJCIS.2014.32","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"","JCRName":"","Score":null,"Total":0}
引用次数: 5
Abstract
A Bloom filter is a simple space-efficient randomized data structure used to represent set in order to support membership queries. So it is very useful to search the wanted data from the all entries. In this paper, we analyze the probability of the false positive rate of the Bloom filter used in various applications up to now and present the revised false positive rate of Bloom filter.
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