THREAT PREVENTION IN SDLC USING ARTIFICIAL INTELLIGENCE

Abstract SDLC (Software development lifecycle) is essentially a series of steps or phases that provide a framework for developing software and managing software throughout its lifecycle. A robust SDLC strategy delivers higher quality software, fewer vulnerabilities, and less time and resources. Not only does it help to develop and maintain software, it also provides an advantage when it comes to obsolete code. The Software Development Life Cycle (SDLC) is a series of phases that provide a common understanding of the software build process. It includes all the phases needed to ensure the development of useful and powerful software products, and involves cost-effective and traceable processes.SDLC takes the responsibility of success and failure of the real time projects. If planned well, even the preliminary phase can set aside a bundle of effort as well as money. With the growth of time and advancements, the reusability of products is seen often in the research and development industry. Reusing components of a code or data does not ensure the security of the project. Threat modeling and risk assessment are considered for different principles. The amalgamation of risk assessment and threat modeling process lessens the risk for software based system. The incorporation of security in each phase for SDLC is a tedious job. This paper focuses on the development of a framework which can prevent threat by using the SDLC process and its components. The paper utilizes the concept of Artificial Intelligence (AI) in combination with OOPS metrics to identify whether the components of a project are safe from threat or not. The judgment parameters are precision, recall and prediction accuracy. KEYWORDS: SDLC,Threat, Artificial Intelligence, Accuracy