Results 251 to 260 of about 696,655 (295)
On the Privacy of Counting Bloom Filters
IEEE Transactions on Dependable and Secure Computing, 2023 Bloom filters are widely used in networking and computing to accelerate membership checking. In many applications filters store sensitive data, so their privacy is of primary concern. At first glance, it seems that extracting the set of elements inserted from the filter would not be possible, because in Bloom filters elements are mapped to positions ...
Shanshan Liu +2 more
exaly +3 more sources
Bloofi: Multidimensional Bloom filters [PDF]
Information Systems, 2015 Bloom filters are probabilistic data structures commonly used for approximate membership problems in many areas of Computer Science (networking, distributed systems, databases, etc.). With the increase in data size and distribution of data, problems arise where a large number of Bloom filters are available, and all them need to be searched for ...
Adina Crainiceanu, Daniel Lemire
exaly +4 more sources
Some of the next articles are maybe not open access.
Related searches:
Related searches:
On the analysis of Bloom filters
Information Processing Letters, 2018zbMATH Open Web Interface contents unavailable due to conflicting licenses.
Fabio Grandi
exaly +5 more sources
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.
Lim Hyesook, Changhoon Yim, Jungwon Lee
exaly +2 more sources
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 +3 more
openaire +2 more sources
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
openaire +2 more sources
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
openaire +2 more sources
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
openaire +2 more sources
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
openaire +2 more sources
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
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source
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
openaire +1 more source
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