Design and Development of Artificial Intelligence Knowledge Processing System for Optimizing Security of Software Systems
TL;DR
Results show significant improvement in threat detection accuracy, response time, and overall system resilience, suggesting that AI-based KPS can be a powerful tool in the software security domain.
Abstract
As software systems continue to evolve in complexity, ensuring their security has become an increasingly critical challenge. Traditional security approaches often fail to adapt to dynamic threat landscapes and sophisticated cyber-attacks. This paper presents the design and development of an Artificial Intelligence (AI)-driven Knowledge Processing System (KPS) aimed at optimizing the security of software systems. The proposed system leverages AI techniques such as machine learning, natural language processing, and expert systems to analyze threat patterns, detect anomalies, and suggest real-time mitigation strategies. By integrating continuous learning from security data and contextual knowledge, the system enhances decision-making and predictive capabilities for threat prevention and response. This research highlights system architecture, implementation methodology, and experimental validation to demonstrate the system’s efficacy. Results show significant improvement in threat detection accuracy, response time, and overall system resilience, suggesting that AI-based KPS can be a powerful tool in the software security domain.