Blockchain Security

Blockchain security research focuses on safeguarding the integrity and availability of blockchain networks, addressing vulnerabilities that can lead to financial losses and system disruptions. Current efforts concentrate on improving vulnerability detection using advanced machine learning models, such as large language models and recurrent neural networks, to identify and classify attacks targeting smart contracts and the underlying peer-to-peer network. These advancements, along with the development of novel consensus mechanisms like Proof of Deep Learning, aim to enhance the security and efficiency of blockchain systems, impacting various applications from cryptocurrency to secure data management in smart industries. The integration of AI and blockchain security is a particularly active area, addressing ethical concerns and improving fairness in transaction processing.