# Adaptive Cuckoo Filters

arXiv: https://arxiv.org/abs/1704.06818 · HTML: https://mlsanity.com/paper/1704.06818/

## Key facts

- Cited by 3 papers in the map (data through 14 Oct 2026).
- First posted on arXiv 22 Apr 2017.

## Built on by (most cited first, 3 of 3)

- [Daisy Bloom Filters](https://mlsanity.com/paper/2205.14894/) (2022)
- [Proteus: A Self-Designing Range Filter](https://mlsanity.com/paper/2207.01503/) (2022)
- [Adversarially Robust Bloom Filters: Privacy, Reductions, and Open Problems](https://mlsanity.com/paper/2501.15751/) (2025)

## Abstract (arXiv)

We introduce the adaptive cuckoo filter (ACF), a data structure for approximate set membership that extends cuckoo filters by reacting to false positives, removing them for future queries. As an example application, in packet processing queries may correspond to flow identifiers, so a search for an element is likely to be followed by repeated searches for that element. Removing false positives can therefore significantly lower the false positive rate. The ACF, like the cuckoo filter, uses a cuckoo hash table to store fingerprints. We allow fingerprint entries to be changed in response to a false positive in a manner designed to minimize the effect on the performance of the filter. We show that the ACF is able to significantly reduce the false positive rate by presenting both a theoretical model for the false positive rate and simulations using both synthetic data sets and real packet traces.