Development of Advanced AI and Deep Learning Models for Security Patches

Purpose and goal:

By aligning research efforts with the global goals outlined in Agenda 2030, the project seeks to address critical challenges in system security and AI. Specifically, the project focuses on enhancing security systems by utilizing advanced AI techniques to mitigate bias, particularly gender bias, within machine learning models.

Expected results and effects:

The project aims to advance AI capabilities by integrating hidden security patch collection techniques and vulnerability prediction methods. The key objective of this research is to develop robust models capable of identifying and predicting vulnerabilities in open-source software. Approach and implementation:

The results promise to enhance the effectiveness and reliability of software security systems, providing more secure and resilient AI-driven solutions.