Blockchain data breach security and cyberattack prevention

Abstract

Systems, methods, and computer programming products leveraging the use of machine learning, cryptographic keys and blockchain technology for validating blockchain transactions. The disclosed systems, methods and products improve detection of malicious cyberattacks and fraud, while reducing occurrences of falsely invalidated transactions and improving overall blockchain security in both permissioned and permissionless blockchain networks. Classifiers are trained using machine learning and other classification techniques by building a transaction history to learn how to identify suspicious transactions on the blockchain. In permissionless and order-execute models of permissioned blockchains, cryptographic keys are publicly registered to guardians residing out of band, who may co-sign requests and override or resubmit transactions marked as suspicious by the classifiers. In an execute-order model of permissioned blockchains, one-time use keys may be registered with the certificate authority of the blockchain, and used to co-sign transactions that might appear suspicious, preventing false-positive identification of suspicious-looking transactions by the classifier.