Evaluation Performance of Bloom Filter in Blockchain Network

Abstract

A blockchain is a secret, scalability and decentralized p2p network in which all nodes follow similar protocols, preventing any single node from controlling the basic structure. In blockchain, Bloom filters are used to preserve the privacy of lightweight nodes. Bloom filter is a memory efficient randomized data structure to represent a set in order to support associate queries.  Bloom filters offer a trade-off between (elements size in the network and bandwidth) and privacy metrics in untrusted environments. This paper proposes an analysis to evaluate the performance of Bloom filters. The evaluation results are based on the statistical distribution, standard deviation, entropy and y-deniability that are used by the attacker to analysis the leakage of the Bloom filter algorithm. Experimental results show that the degree of privacy in the network needs a large amount of elements and more bandwidth using the Bloom filter algorithm.