An ETCC-based security enhancement in an e-governance cloud environment by trust analysis of users using PA-ChatGPT

Abstract

For developing and less-developed countries, the e-governance system is highly helpful. The public mostly uses the e-governance system; thus, security is highly required. In prevailing studies, the security enhancement of the e-governance cloud application was concentrated. However, a security shortage issue was presented. To solve this issue, this study proposes ETCC-centric secure data storage in e-governance cloud applications. Primarily, the user registers into the server by utilizing their username and password. Next, only the location-matched users are permitted to access the server. Then, the public and private keys are generated by the key generation. Subsequently, by utilizing user behavior extraction, important behavior selection by BMFKO and prediction by ANOVA-based PA-ChatGPT, the trust is analyzed. The predicted abnormal behavior user is blocked. Next, the normal behavior user is permitted to upload and download the data. The data is securely stored by the proposed ETCC technique. The Beta Delegated Proof of Stake (BDPoS) technique considers blockchain for enhancing security. Authorized data user downloads the data and decrypts it with their private key. Based on performance measures, the proposed techniques are analogized with the prevailing techniques in experimental analysis. The security level attained by the proposed technique is 99.2%.