4.5 Article

Bloom Filter With a False Positive Free Zone

Journal

IEEE TRANSACTIONS ON NETWORK AND SERVICE MANAGEMENT
Volume 18, Issue 2, Pages 2334-2349

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TNSM.2021.3059075

Keywords

Base stations; Technological innovation; Hash functions; Testing; Electronic mail; Probabilistic logic; Monitoring; Computer networks; data structures; software defined networking

Funding

  1. Hungarian Scientific ResearchFund [OTKA K115288, K129335, K128062, FK134604, K124171]
  2. Hungarian Ministry of Innovation
  3. National Research, Development and Innovation Office
  4. TKP2020, Institutional Excellence Program of the National Research Development and Innovation Office [BME IE-MI-SC TKP2020]
  5. High Speed Networks Laboratory (HSNLab)
  6. Janos Bolyai Research Scholarship of the Hungarian Academy of Sciences
  7. New National Excellence Program of the Ministry of Human Capacities [UNKP-18-4]
  8. New National Excellence Program of the Ministry for Innovation and Technology [UNKP-19-4]
  9. New National Excellence Program of the Ministry for Innovation and Technology from the source of the national research, development and innovation fund [UNKP-20-5]
  10. Technion Hiroshi Fujiwara Cyber Security Research Center
  11. Israel National Cyber Directorate
  12. Alon fellowship
  13. German-Israeli Science Foundation (GIF) Young Scientists Program
  14. Taub Family Foundation
  15. Polak Fund for Applied Research, at the Technion

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This article discusses the importance of Bloom filters and their variants in networking applications, and introduces a new data structure called EGH filter that guarantees false positive-free operations. The EGH filter supports Bloom filter operations and ensures real-time false positive-free operations within a limited universe and restricted number of elements stored.
Bloom filters and their variants are widely used as space-efficient probabilistic data structures for representing sets and are very popular in networking applications. They support fast element insertion and deletion, along with membership queries with the drawback of false positives. Bloom filters can be designed to match the false positive rates that are acceptable for the application domain. However, in many applications, a common engineering solution is to set the false positive rate very small and ignore the existence of the very unlikely false positive answers. This article is devoted to close the gap between the two design concepts of unlikely and not having false positives. We propose a data structure called EGH filter that supports the Bloom filter operations, and besides, it can guarantee false positive free operations for a finite universe and a restricted number of elements stored in the filter. We refer to the limited universe and filter size as the false positive free zone of the filter. We describe necessary conditions for the false-positive free zone of a filter. We then generalize the filter to support the listing of the elements through the use of counters rather than bits. We detail networking applications of the filter and discuss potential generalizations. We evaluate the performance of the filter in comparison with the traditional Bloom filters. We also evaluate the price in terms of memory that needs to be paid to guarantee real false positive-free operations for having a deterministic Bloom filter-like behavior. Our data structure is based on recently developed combinatorial group testing techniques.

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