Cuckoo Filter Approach for an Efficient Tainted Bitcoin Identification

Abstract

Bitcoin has become one of the most popular cryptocurrency and it is the first and foremost cryptocurrency that comes to play as an alternative to the traditional currency. Even though bitcoins have lots of advantages a certain group of people tend to use these bitcoins for illegal purposes. So there comes the need of identifying these bitcoins before their usage. Probabilistic approach has been taken through this research in order to make this tainted bitcoin identification efficient. Cuckoo filter has a better performance when compared to other probabilistic data structures. This is the very first occasion that Cuckoo filters have been taken for bitcoin and blockchain analysis purposes. The evaluation of the Cuckoo filter is conducted with respect to time and space consumption by utilizing some accepted space and time consumption measuring tools. Through this research it is successfully showed that tainted bitcoin identification process can be made efficient mainly with respect to time, where the authenticity of a given transaction can be checked in constant time by preserving its accuracy rate with the aid of Cuckoo filters. Additionally, deletion of tainted transactions from the data structure also can be done with Cuckoo filters. Therefore, the proposed tainted bitcoin identification with Cuckoo filter approach, can be considered as a significant contribution to the body of knowledge.