AI and Blockchain-based source code vulnerability detection and prevention system for multiparty software development

Abstract

With the growing demand for application software , there is a race among industries to develop software as quickly as possible. However, maintaining pace and ensuring bug-free software has become increasingly challenging in a work-from-home arrangement as software developers are not under constant supervision. It increases the possibility of buggy products, and traditional testing techniques fail to provide optimal performance . We propose an Artificial Intelligence (AI) and blockchain-based novel decentralized software testing system. The proposed system aims to detect and prevent vulnerable code by synergizing deep learning capabilities and smart-contract-powered blockchain . The vulnerability detection is performed automatically without relying on manually written rules. We propose a non-vulnerability score range map to classify the source code . Furthermore, we integrate an InterPlanetary File System (IPFS) to ensure efficient storage over the blockchain . We conduct a testbed-based experiment to demonstrate the effectiveness of AI and blockchain integration for secure code development and testing.