MUMBAI, India, April 17 -- Intellectual Property India has published a patent application (202641043178 A) filed by Cvr College Of Engineering, Hyderabad, Telangana, on April 4, for 'ai-driven deep learning framework for real-time vulnerability detection in blockchain smart contracts.'
Inventor(s) include Vankudoth Ramesh.
The application for the patent was published on April 17, under issue no. 16/2026.
According to the abstract released by the Intellectual Property India: "To the smart contract deployment by using blockchain platforms are increasing exposed to securities vulnerabilities such as reentrancy, integer overflow, and denial-of-service attacks. Existing solution given mainly dependent on static analysis tool and manual auditing process, which is a time-consuming, limited scalability, and often ineffectively in detect complex or zero-day threats. To proposed AI-driven deep learning framework introduced a real-time vulnerabilities detection system using by the neural network model trained on smart contracts bytecode and source code patterns. The frameworks integrate feature extractions, graph-based code representations, and automated risk taxonomy technique to improve detection accurateness and threat proof of identity. Unlike the traditionally used rule-based methods, the system continuously enhanced its performance through adaptive learning and large-scale blockchain data analysis. The new model enables proactive securities monitoring and automatically auditing across decentralize platforms, in technique strengthening blockchain reliability through intelligent, scalable, and real-time smart contract security system."
Disclaimer: Curated by HT Syndication.
