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The Bloom filter (BF) is a space efficient randomized data structureparticularly suitable to represent a set supporting approximate membershipqueries. BFs have been extensively used in many applications especially innetworking due to their simplicity and flexibility. The performances of BFsmainly depends on query overhead, space requirements and false positives. Theaim of this paper is to focus on false positives. Inspired by the recentapplication of the BF in a novel multicast forwarding fabric for informationcentric networks, this paper proposes the yes-no BF, a new way of representinga set, based on the BF, but with significantly lower false positives and nofalse negatives. Although it requires slightly more processing at the stage ofits formation, it offers the same processing requirements for membershipqueries as the BF. After introducing the yes-no BF, we show throughsimulations, that it has better false positive performance than the BF.

Yes-no Bloom filter: A way of representing sets with fewer false positives