The research proposes a framework called SecNet for ensuring the safety of data over its lifecycle via the Internet at scale. The widespread dispersion of data across digital spaces has rendered authentication and authorization of its usage difficult. The proposed architecture is comprised of three primary elements: In order to generate authentic big data, blockchain-based data exchange with ownership guarantee is necessary. Blockchain technology makes it possible to verify the authenticity of the data and trace it back to its original creator. Data encryption enabled by artificial intelligence: This system has the potential to create a more secure and trustworthy digital ecosystem by developing more nuanced security rules. When used to cyber security, AI has the potential to discover new vulnerabilities and flaws in the system. The effectiveness of AI may be improved if individuals were incentivized to share their data via the establishment of a trustworthy system for exchanging monies in exchange for the supply of a security service. This article compares and contrasts the typical SecNet implementation with some of its alternatives. We also analyze the repercussions on network security and revenue generation. Overcoming the challenges of allowing data interchange through the internet is central to the proposed architecture, which aims to boost AI performance utilizing real-world huge data.