Enhancing Security by Integrating Blockchain with FNN, a Sustainable Solution

Blockchain is a decentralized, immutable ledger system that can help in securing one’s stored information. In data security, a Feedforward Neural Network is utilized to enhance threat detection and anomaly identification. This type of neural network is trained on historical data to recognize patterns associated with security threats, such as unusual network activities or unauthorized access attempts. Integrating Blockchain with a Feedforward Neural Network combines the strengths of both technologies. This research paper is an effort to integrate blockchain with feedforward neural networks for improving the security of healthcare data in industrial cyberphysical systems. The results of the experiments demonstrate that integrating blockchain with a Feedforward Neural Network (FNN) can be achieved without compromising model accuracy. Furthermore, the integration aligns with sustainability principles by promoting efficient resource usage and contributing to secure, scalable, and resilient digital infrastructures, in line with the Sustainable Development Goals (SDGs). Notably, experimental results show that integrating Blockchain with FNN can be achieved without compromising model accuracy while slightly reducing training time, suggesting that blockchain integration can enhance system efficiency and sustainability by optimizing computational and energy resources.