Results 21 to 30 of about 20,075 (258)
eBF: an enhanced Bloom Filter for intrusion detection in IoT
Journal of Big Data, 2023 Intrusion Detection is essential to identify malicious incidents and continuously alert many users of the Internet of Things (IoT). The constant monitoring of events generated from many devices connected to the IoT and the extensive analysis of every ...
Fitsum Gebreegziabher Gebretsadik +2 more
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The Bloom paradox: When not to use a Bloom filter? [PDF]
2012 Proceedings IEEE INFOCOM, 2012 In this paper, we uncover the Bloom paradox in Bloom Filters: Sometimes, the Bloom Filter is harmful and should not be queried. We first analyze conditions under which the Bloom paradox occurs in a Bloom Filter and demonstrate that it depends on the a priori probability that a given element belongs to the represented set. We show that the Bloom paradox
Ori Rottenstreich, Isaac Keslassy
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Hunting the Pertinency of Bloom Filter in Computer Networking and Beyond: A Survey
Journal of Computer Networks and Communications, 2019 Bloom filter is a probabilistic data structure to filter a membership of a set. Bloom filter returns “true” or “false” with an error tolerance depending on the presence of the element in the set.
Ripon Patgiri +2 more
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Bloom Filters in Adversarial Environments [PDF]
ACM Transactions on Algorithms, 2015 Many efficient data structures use randomness, allowing them to improve upon deterministic ones. Usually, their efficiency and correctness are analyzed using probabilistic tools under the assumption that the inputs and queries are independent of the internal randomness of the data structure.
Moni Naor, Eylon Yogev
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Adaptive Compression Trie Based Bloom Filter: Request Filter for NDN Content Store
IEEE Access, 2017 In named data networking (NDN), content store (CS) is proposed to provide on-path cache service. When user's request with content name is forwarded to NDN node, exact match in CS is carried out first.
Ran Zhang +4 more
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Partitioned Learned Bloom Filter
CoRR, 2020 Bloom filters are space-efficient probabilistic data structures that are used to test whether an element is a member of a set, and may return false positives. Recently, variations referred to as learned Bloom filters were developed that can provide improved performance in terms of the rate of false positives, by using a learned model for the ...
Kapil Vaidya +3 more
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Hash Adaptive Bloom Filter [PDF]
2021 IEEE 37th International Conference on Data Engineering (ICDE), 2021 Bloom filter is a compact memory-efficient probabilistic data structure supporting membership testing, i.e., to check whether an element is in a given set. However, as Bloom filter maps each element with uniformly random hash functions, few flexibilities are provided even if the information of negative keys (elements are not in the set) are available ...
Rongbiao Xie +6 more
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A Case for Partitioned Bloom Filters
IEEE Transactions on Computers, 2023 In a partitioned Bloom Filter the $m$ bit vector is split into $k$ disjoint $m/k$ sized parts, one per hash function. Contrary to hardware designs, where they prevail, software implementations mostly adopt standard Bloom filters, considering partitioned filters slightly worse, due to the slightly larger false positive rate (FPR).
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A Distance-Encoded Bloom Filter for Fast NDN Name Lookup
Applied SciencesNamed data networking (NDN) is a content-centric network architecture that requires efficient name lookup to forward packets based on hierarchical content names.
Junghwan Kim, Myeong-Cheol Ko
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Applied Sciences, 2020 Because the development of the Internet of Things (IoT) requires technology that transfers information between objects without human intervention, the core of IoT security will be secure authentication between devices or between devices and servers ...
Jungwon Lee +4 more
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