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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
openaire +3 more sources
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 ...
Pedro Reviriego +5 more
openaire +2 more sources
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
doaj +1 more source
Low-power bloom filter architecture for deep packet inspection [PDF]
, 2006 Bloom filters are frequently used to identify malicious content like viruses in high speed networks. However, architectures proposed to implement bloom filters are not power efficient.
Kaya, I, Kocak, T
core +2 more sources
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
openaire +1 more source
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
doaj +1 more source
Towards practical use of Bloom Filter based IP lookup in operational network [PDF]
, 2014 International audienceBloom Filter is a widely used data structure in computer science. It enables memory efficient and fast set membership queries. Bloom filter-based solutions have been proposed in the past decade for lookup in forwarding tables of ...
Duan, Ruian +4 more
core +4 more sources
Design of a multiple bloom filter for distributed navigation routing [PDF]
, 2013 Unmanned navigation of vehicles and mobile robots can be greatly simplified by providing environmental intelligence with dispersed wireless sensors. The wireless sensors can work as active landmarks for vehicle localization and routing. However, wireless
Cheng, Yongqiang +4 more
core +1 more source
Throughput analysis for a high-performance FPGA-accelerated real-time search application [PDF]
, 2012 We propose an FPGA design for the relevancy computation part of a high-throughput real-time search application. The application matches terms in a stream of documents against a static profile, held in off-chip memory.
Chalamalasetti, S.R. +2 more
core +3 more sources
Optimized hash for network path encoding with minimized false positives [PDF]
, 2014 The Bloom filter is a space efficient randomized data structure for representing a set and supporting membership queries. Bloom filters intrinsically allow false positives.
Carrea, Laura +2 more
core +1 more source