Results 211 to 220 of about 20,075 (258)
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Ternary Bloom Filter Replacing Counting Bloom Filter
IEEE Communications Letters, 2017A counting Bloom filter (CBF) is commonly used in many applications for the membership queries of dynamic data since the CBF can provide delete operations. A CBF uses an array of $c$ -bit counters. The $c$ should be large enough to avoid overflows.
Hyesook Lim +2 more
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Complement Bloom Filter for Identifying True Positiveness of a Bloom Filter
IEEE Communications Letters, 2015The use of Bloom filters in network applications has increased rapidly. Since Bloom filters can produce false positives, the trueness of each positive needs to be identified by referring to an off-chip hash table. This letter proposes a new method for identifying the trueness of Bloom filter positives.
Hyesook Lim, Changhoon Yim
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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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2008 Proceedings IEEE INFOCOM - The 27th Conference on Computer Communications, 2008
A bloom filter is a randomized data structure for performing approximate membership queries. It is being increasingly used in networking applications ranging from security to routing in peer to peer networks. In order to meet a given false positive rate, the amount of memory required by a bloom filter is a function of the number of elements in the set.
Fang Hao +2 more
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A bloom filter is a randomized data structure for performing approximate membership queries. It is being increasingly used in networking applications ranging from security to routing in peer to peer networks. In order to meet a given false positive rate, the amount of memory required by a bloom filter is a function of the number of elements in the set.
Fang Hao +2 more
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IEEE Transactions on Knowledge and Data Engineering, 2010
A Bloom filter is an effective, space-efficient data structure for concisely representing a set, and supporting approximate membership queries. Traditionally, the Bloom filter and its variants just focus on how to represent a static set and decrease the false positive probability to a sufficiently low level.
Deke Guo +4 more
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A Bloom filter is an effective, space-efficient data structure for concisely representing a set, and supporting approximate membership queries. Traditionally, the Bloom filter and its variants just focus on how to represent a static set and decrease the false positive probability to a sufficiently low level.
Deke Guo +4 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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2019 International Conference on Electronics, Information, and Communication (ICEIC), 2019
A membership identification is a key functionality in many network applications. Various data structures have been introduced in order to support the efficient membership identification. Since a Bloom filter can provide simple but efficient membership checking, it is widely used in many network applications.
Ju Hyoung Mun, Hyesook Lim
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A membership identification is a key functionality in many network applications. Various data structures have been introduced in order to support the efficient membership identification. Since a Bloom filter can provide simple but efficient membership checking, it is widely used in many network applications.
Ju Hyoung Mun, Hyesook Lim
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Effect of Hadamard multiplication on bloom filter and double bloom filter transformations
SECURITY AND PRIVACY, 2023AbstractIris biometric is the most common and widely accepted biometric authentication method due to its high accuracy. The iris biometric template should be protected to overcome security and privacy attacks. The two standard iris biometric template protection methods are bloom filter and double bloom filter‐based feature transformations.
Ajish Sreedharan, K. S. Anil Kumar
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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
openaire +1 more source