A survey of Blockchain security, Artificial Intelligence and Homomorphic encryption

In various applications, blockchain technology has emerged as a viable alternative for safe and transparent record-keeping. However, because of possible vulnerabilities such as cyber assaults, data breaches, and unauthorized access, the security of blockchain networks remains a major worry. To solve these issues, academics have advocated incorporating AI and homomorphic encryption methods into blockchain systems to improve security and privacy. AI can deliver intelligent threat detection and mitigation capabilities to detect and prevent security breaches in real time. AI can evaluate enormous amounts of data using anomaly detection, pattern recognition, and predictive analytics to find unusual patterns and behaviors that may suggest possible attacks or weaknesses in the blockchain network. AI may also improve privacy in blockchain systems by anonymizing transaction data and safeguarding user identities, lowering the danger of data breaches and unwanted access. On the other hand, homomorphic encryption enables the safe computation of encrypted data without decryption, maintaining the data's secrecy and integrity throughout the process. This is especially useful in blockchain systems where data privacy is crucial. Homomorphic encryption enables safe and private transactions, smart contracts, and data exchange across blockchain network users without exposing the data in plaintext to unauthorized organizations.

A survey of Blockchain security, Artificial Intelligence and Homomorphic encryption Keywords:

Blockchain , Homomorphic , Artificial Intelligence , Encryption method