Name
Title | ||
|---|---|---|
Analyzing and Assessing Pollution Attacks on Bloom Filters: Some Filters are More Vulnerable than Others |
Abstract | ||
|---|---|---|
Bloom filters are probabilistic data structures that are popular in networking for set representation; however, they show an inherent inaccuracy due to false positives. One of the potential attacks on Bloom filters is to pollute them with elements that cause the filter to have a larger false positive probability than under normal operation; Pollution is simple when an attacker knows the details of... |
Year | DOI | Venue |
|---|---|---|
2021 | 10.23919/CNSM52442.2021.9615566 | 2021 17th International Conference on Network and Service Management (CNSM) |
Keywords | DocType | ISBN |
Bloom Filters,Security,Pollution attacks,Black-box adversaries | Conference | 978-3-903176-36-2 |
Citations | PageRank | References |
0 | 0.34 | 0 |
Authors | ||
4 | ||
Name | Order | Citations | PageRank |
|---|---|---|---|
| Pedro Reviriego | 1 | 0 | 1.35 |
| Ori Rottenstreich | 2 | 9 | 7.31 |
| Shanshan Liu | 3 | 5 | 4.50 |
| Fabrizio Lombardi | 4 | 57 | 10.81 |