Invertible bloom lookup tables

By Michael T. Goodrich, Michael M. Mitzenmacher. 2011

251 citations recorded by the source corpus.

We present a version of the Bloom filter data structure that supports not only the insertion, deletion, and lookup of key-value pairs, but also allows a complete listing of the pairs it contains with high probability, as long the number of key-value pairs is below a designed threshold. Our structure allows the number of key-value pairs to greatly exceed this threshold during normal operation. Exceeding the threshold simply temporarily prevents content listing and reduces the probability of a successful lookup. If entries are later deleted to return the structure below the threshold, everything again functions appropriately. We also show that simple variations of our structure are robust to certain standard errors, such as the deletion of a key without a corresponding insertion or the insertion of two distinct values for a key. The properties of our structure make it suitable for several applications, including database and networking applications that we highlight.

Subfields: Artificial Intelligence, Computer Networks and Communications

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Citations in the corpus

Secure Single-Server Aggregation with (Poly)Logarithmic Overhead (2020, methodology): “We address the issues in the above protocol, i.e. for settings where the size of the message domainm is much larger than the number of clientn by leveraging a probabilistic data structure called an invertible Bloom lookup table (IBLT) [21].”
Elastic sketch: adaptive and fast network-wide measurements (2018, methodology): “For FlowRadar, we use 3 hash functions in both the Bloom filter [44] and the IBLT part [45]; we allocate 1/10 of the memory for the Bloom filter and the rest for IBLT.”
FlowRadar: A Better NetFlow for Data Centers (2016, methodology): “Our single node encoding scheme is similar to IBLT’s, but takes much less time because of the simple FlowXOR and FlowCount fields.”
"Better Than Nothing" Privacy with Bloom Filters: To What Extent? (2012, background): “Note that in some scenarios, the ability to invert a Bloom filter comes as a functional advantage: indeed [27] proposes a Bloom filter enhancement where extra information permits to list the complete filter’s content with high probability.”