Examine Of Algorithmic Approaches To Software Security

The complexity of threats in the virtual world is growing, so new solutions are required for software protection. Artificial Intelligence has become a leading factor in strengthening software security against constantly changing threats. This extensive review synthesizes the current progress and trends for algorithmic AI methodologies in context of software protection. Specifically, we discuss requesting machine learning techniques and neural networks used for threat detection, vulnerability assessment, and adaptive defense mechanisms as well as using evolutionary algorithms. From this, we can deduce that security systems that AI enhances are much more flexible and efficient than traditional security. Zero-day vulnerabilities can be detected by deep learning models with high accuracy and reinforcement learning algorithms are effective in real-time threat handling. AI opens up opportunities in the software security domain as a predictor of vulnerability, yet there are shortcomings related to model interpretability and adversarial robustness. More detailed studies are needed to work on the more transparent models of artificial intelligence and to incorporate those into existing security systems. © 2024 IEEE.