Optimizing bloom filter: Challenges, solutions, and comparisons
Bloom filter (BF) has been widely used to support membership query, ie, to judge whether a
given element x is a member of a given set S or not. Recent years have seen a flourish …
given element x is a member of a given set S or not. Recent years have seen a flourish …
Theory and practice of bloom filters for distributed systems
S Tarkoma, CE Rothenberg… - … Surveys & Tutorials, 2011 - ieeexplore.ieee.org
Many network solutions and overlay networks utilize probabilistic techniques to reduce
information processing and networking costs. This survey article presents a number of …
information processing and networking costs. This survey article presents a number of …
When private set intersection meets big data: an efficient and scalable protocol
Large scale data processing brings new challenges to the design of privacy-preserving
protocols: how to meet the increasing requirements of speed and throughput of modern …
protocols: how to meet the increasing requirements of speed and throughput of modern …
Discrete-continuous optimization for large-scale structure from motion
Recent work in structure from motion (SfM) has successfully built 3D models from large
unstructured collections of images downloaded from the Internet. Most approaches use …
unstructured collections of images downloaded from the Internet. Most approaches use …
Linking sensitive data
Sensitive personal data are created in many application domains, and there is now an
increasing demand to share, integrate, and link such data within and across organisations in …
increasing demand to share, integrate, and link such data within and across organisations in …
Scalable bloom filters
Bloom filters provide space-efficient storage of sets at the cost of a probability of false
positives on membership queries. The size of the filter must be defined a priori based on the …
positives on membership queries. The size of the filter must be defined a priori based on the …
Less hashing, same performance: Building a better bloom filter
A Kirsch, M Mitzenmacher - Algorithms–ESA 2006: 14th Annual European …, 2006 - Springer
A standard technique from the hashing literature is to use two hash functions h 1 (x) and h 2
(x) to simulate additional hash functions of the form gi (x)= h 1 (x)+ ih 2 (x). We demonstrate …
(x) to simulate additional hash functions of the form gi (x)= h 1 (x)+ ih 2 (x). We demonstrate …
Practical multi-party private set intersection protocols
A Bay, Z Erkin, JH Hoepman… - IEEE Transactions on …, 2021 - ieeexplore.ieee.org
Privacy-preserving techniques for processing sets of information have attracted the research
community's attention in recent years due to society's increasing dependency on the …
community's attention in recent years due to society's increasing dependency on the …
[HTML][HTML] Double-blockchain assisted secure and anonymous data aggregation for fog-enabled smart grid
As a future energy system, the smart grid is designed to improve the efficiency of traditional
power systems while providing more stable and reliable services. However, this efficient and …
power systems while providing more stable and reliable services. However, this efficient and …
Partitioned learned bloom filter
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 …
element is a member of a set, and may return false positives. Recently, variations referred to …