Data breach Analysis for Financial Smart Contracts

Abstract

In the same way that personal data provide irrefutable information about individuals, they sometimes reveal the legal identity of contracts as well as other specific information. The data a contract generates could represent a competitive advantage. This study's focus was to develop a template of the factors associated with smart contracts data breaches. This model was based on the following variables: smart contracts, exposure level, security level, and structural inputs. The outcome variable was the binary value for a data breach/no data breach. This study covers more than 6000 smart contracts, operating on Etheurm and imported as tables into the study database, the contracts have been selected randomly from the databases of various safety tools such as OYENTE, MAIAN, GASPER, Securify, Solcove, and SmartCheck, These tools are designed to find code vulnerabilities in the smart contracts. 50% of all samples were selected from one source (Securify). Binary logistic regression was employed to examine the data breach model. The findings demonstrate more than 500 cases of actual breaches, with several factors being significantly associated with smart contract data breaches.