AI and Blockchain-based source code vulnerability detection and prevention system for multiparty software development. (March 2023) - Nath, Panchanan; Mushahary, Jaya Rani; Roy, Ujjal; Brahma, Maharaj; Singh, Pranav Kumar
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. Graphical abstract: Highlights: Software testing is one of the vital phases in the software development life cycle. AI can automate the code testing process for vulnerability detection. A blockchain-based system ensures transparency and trust in software development. Integrating AI and Blockchain can enhance the software testing lifecycle.