Providing a New Framework for Secure Software Development Using AI Techniques in the No -Code Process and Testing

In today's world, software security is considered as one of the main challenges in the development of information systems. Due to the increase in cyber threats and complex attacks, the need for new methods for developing secure software is felt more than ever. This paper presents a new framework for developing secure software using artificial intelligence techniques in the coding and testing stages. The proposed framework consists of three main steps: Code analysis: In this step, machine learning algorithms are used to identify potential vulnerabilities in the source code. By analyzing coding patterns and identifying weaknesses, developers can be helped to write more secure code. Automated testing: Using AI techniques, the software testing process is automated. These techniques include anomaly-based testing and simulation of cyberattacks, which can help identify software weaknesses and vulnerabilities in the early stages of development. Prediction and Improvement: This step involves using predictive models to identify and assess security risks in developing software. By analyzing historical data and identifying attack patterns, developers can be provided with recommendations to improve software security. The results of the experiments show that the use of this new framework can lead to a significant reduction in the number of vulnerabilities in the software and improve the quality and security of the developed software. This paper also addresses the challenges and limitations in the implementation of this framework and provides solutions to overcome them. Finally, this research is considered as an important step towards the development of secure and resistant software against cyber threats.

کلیدواژه ها:

Novice Code ، Internet of Things ، Secure Software Development ، Artificial Intelligence ، AI