Integrating AI and Blockchain Technologies for Advanced Threat Detection and Secure Data Management in Cyber Ecosystems

The nature of cyber threats is advancing at a phenomenal pace and thus advanced solutions based on artificial intelligence and blockchain technology are needed. Security systems in existence have scalability, real-time threat detection and data integrity problems. The contribution of this research is a hybrid AI Blockchain framework with a higher level of threat detection and data security. Specialized algorithms, that use artificial intelligence, search through cyber threats, while the block chain makes it possible to ensure the tamper-proof storing of all the data. Such methods include usage of smart contracts, user entity and behavior analysis and anomaly detection techniques. The merger is useful in improving detection accuracy, response time, data integrity. The model is proven to be effective for real-world dataset experiments and detection accuracy is improved with fewer false positives. At the same time, the system includes a blockchain emulator, Ganache, which allows to set up a local Ethereum blockchain environment for connecting to Web3.