BLOCKCHAIN DATA BREACH SECURITY AND CYBERATTACK PREVENTION

Organization Name

INTERNATIONAL BUSINESS MACHINES CORPORATION

Inventor(s)

BLOCKCHAIN DATA BREACH SECURITY AND CYBERATTACK PREVENTION - A simplified explanation of the abstract

This abstract first appeared for US patent application 20240048582 titled 'BLOCKCHAIN DATA BREACH SECURITY AND CYBERATTACK PREVENTION

Simplified Explanation

The patent application describes systems, methods, and computer programming products that utilize machine learning, cryptographic keys, and blockchain technology to validate blockchain transactions. These innovations aim to enhance the detection of malicious cyberattacks and fraud, while reducing 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 analyzing 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. These guardians may co-sign requests, override or resubmit transactions marked as suspicious by the classifiers.
In an execute-order model of permissioned blockchains, one-time use keys can be registered with the blockchain's certificate authority. These keys are used to co-sign transactions that may appear suspicious, preventing false-positive identification of suspicious-looking transactions by the classifier.

Potential Applications:

Enhancing the security and trustworthiness of blockchain transactions in various industries such as finance, supply chain, healthcare, and more.
Improving fraud detection and prevention in blockchain-based systems.
Strengthening the security of permissioned blockchain networks by leveraging machine learning and cryptographic techniques.

Problems Solved:

Detection and prevention of malicious cyberattacks and fraud in blockchain transactions.
Reduction of falsely invalidated transactions, minimizing disruptions and improving the efficiency of blockchain networks.
Enhancing the overall security and trustworthiness of blockchain-based systems.

Benefits:

Increased security and trust in blockchain transactions, leading to improved confidence in blockchain technology.
Enhanced fraud detection capabilities, reducing financial losses and protecting users' assets.
Improved efficiency and reliability of blockchain networks by minimizing false positives and false negatives in transaction validation.

Original Abstract Submitted

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.

20240048582. BLOCKCHAIN DATA BREACH SECURITY AND CYBERATTACK PREVENTION simplified abstract (INTERNATIONAL BUSINESS MACHINES CORPORATION)

Contents

BLOCKCHAIN DATA BREACH SECURITY AND CYBERATTACK PREVENTION

Organization Name

Inventor(s)