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2006 IEEE International Symposium on Information Theory, 2006
A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applications. In this paper, we generalize the traditional Bloom filter to Weighted Bloom Filter, which incorporates the ...
Jehoshua Bruck +2 more
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A Bloom filter is a simple randomized data structure that answers membership query with no false negative and a small false positive probability. It is an elegant data compression technique for membership information and has broad applications. In this paper, we generalize the traditional Bloom filter to Weighted Bloom Filter, which incorporates the ...
Jehoshua Bruck +2 more
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Proceedings of the 2003 ACM SIGMOD international conference on Management of data, 2003
A Bloom Filter is a space-efficient randomized data structure allowing membership queries over sets with certain allowable errors. It is widely used in many applications which take advantage of its ability to compactly represent a set, and filter out effectively any element that does not belong to the set, with small error probability.
Saar Cohen 0002, Yossi Matias
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A Bloom Filter is a space-efficient randomized data structure allowing membership queries over sets with certain allowable errors. It is widely used in many applications which take advantage of its ability to compactly represent a set, and filter out effectively any element that does not belong to the set, with small error probability.
Saar Cohen 0002, Yossi Matias
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2016 IEEE 2nd International Conference on Collaboration and Internet Computing (CIC), 2016
A Bloom filter is a space-efficient probabilistic data structure that is used in many domains including networking applications to test for set memberships. Such applications often require sending Bloom filters using messages. Consequently, it is important to minimize the size of the filters such that the storage, transmission, and processing costs are
Negar Mosharraf +2 more
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A Bloom filter is a space-efficient probabilistic data structure that is used in many domains including networking applications to test for set memberships. Such applications often require sending Bloom filters using messages. Consequently, it is important to minimize the size of the filters such that the storage, transmission, and processing costs are
Negar Mosharraf +2 more
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Proceedings of the 2017 VI International Conference on Network, Communication and Computing, 2017
A standard technique from the cryptanalysis is to use exhaustive search that consists of systematically enumerating all possible candidates for the solution and checking whether each candidate satisfies the hash value. But this will take a lot of storage space and the time spent on query will be very long.
Yuanhang Yang, Shuhui Chen
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A standard technique from the cryptanalysis is to use exhaustive search that consists of systematically enumerating all possible candidates for the solution and checking whether each candidate satisfies the hash value. But this will take a lot of storage space and the time spent on query will be very long.
Yuanhang Yang, Shuhui Chen
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IEEE/ACM Transactions on Networking, 2001
A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, for many applications the space savings outweigh this draw-back when the probability of an error is sufficiently low.
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A Bloom filter is a simple space-efficient randomized data structure for representing a set in order to support membership queries. Although Bloom filters allow false positives, for many applications the space savings outweigh this draw-back when the probability of an error is sufficiently low.
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On the analysis of Bloom filters
Information Processing Letters, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
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A Bloom filter variant for Blockchain
Concurrency and Computation: Practice and Experience, 2021AbstractBlockchain is a single linked list of blocks consisting of transactions identified by their hash value. Querying Blockchain, primarily searching blocks/transactions, can be treated as membership queries and efficiently evaluated by a Bloom filter (BF).
Xing Fan, Baoning Niu
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2015
Modern databases tailored to highly distributed, fault tolerant management of information for big data applications exploit a classical data structure for reducing disk and network I/O as well as for managing data distribution: The Bloom filter. This data structure allows to encode small sets of elements, typically the keys in a key-value store, into a
Martin Werner 0001, Mirco Schönfeld
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Modern databases tailored to highly distributed, fault tolerant management of information for big data applications exploit a classical data structure for reducing disk and network I/O as well as for managing data distribution: The Bloom filter. This data structure allows to encode small sets of elements, typically the keys in a key-value store, into a
Martin Werner 0001, Mirco Schönfeld
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PFBF: Pre-Filtered Bloom Filters
2015In this paper we focus on improving the false positive rate of a bloom filter with a pre-filtering scheme. By applying this scheme on a bloom filter, we can quickly screen out lots of input before entering the bloom filter and hence improve the result of false positives.
Ssu-Ting Liu, Sheng-De Wang
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L-priorities bloom filter: A new member of the bloom filter family
International Journal of Automation and Computing, 2012A Bloom filter is a space-efficient data structure used for concisely representing a set as well as membership queries at the expense of introducing false positive. In this paper, we propose the L-priorities Bloom filter (LPBF) as a new member of the Bloom filter (BF) family, it uses a limited multidimensional bit space matrix to replace the bit vector
Huangshui Hu, Hongwei Zhao, Fei Mi
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