Name
Title | ||
|---|---|---|
Learned Bloom Filters in Adversarial Environments: A Malicious URL Detection Use-Case |
Abstract | ||
|---|---|---|
Learned Bloom Filters (LBFs) have been recently proposed as an alternative to traditional Bloom filters that can reduce the amount of memory needed to achieve a target false positive probability when representing a given set of elements. LBFs rely on Machine Learning models combined with traditional Bloom filters. However, if LBFs are going to be used as an alternative to Bloom filters, their secu... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.1109/HPSR52026.2021.9481857 | 2021 IEEE 22nd International Conference on High Performance Switching and Routing (HPSR) |
Keywords | DocType | ISBN |
Learned Bloom Filters,Machine Learning,Security | Conference | 978-1-6654-4005-9 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pedro Reviriego | 1 | 0 | 1.35 |
| José Alberto Hernández | 2 | 1 | 1.16 |
| Zhenwei Dai | 3 | 0 | 0.34 |
| Anshumali Shrivastava | 4 | 0 | 0.34 |