Application of Artificial Intelligence in Threat Detection and Malware Analysis

Given that networks are a crucial element of modern life, all devices connected to them are constantly at risk of attack by a third party with outside knowledge. Once the network layer is breached, an attacker may be able to eavesdrop on network traffic and collect sensitive data, and with such activity going on nearby, a security expert cannot simply wait for an attack to occur. Threat hunting is used to detect vulnerabilities, fix them before someone can exploit them, and take preventative measures, which enables the cyber team to proactively discover vulnerabilities by fusing knowledge and artificial intelligence to stop any attack before it can do significant harm. It is crucial to understand the behaviour and patterns of current malware in order to develop countermeasures that will help to neutralize unidentified threats and be ready for new attacks. In order to train the model to distinguish between good and harmful patterns, one can prepare the system by undertaking malware analysis. This will reduce false positives and boost protection. The goal of this research is to identify various types and techniques for enhancing network security or device security by combining artificial intelligence, malware analysis, and threat hunting. This article also compares traditional approaches with AI-based strategies to list all the benefits that can be obtained by combining traditional methods with artificial intelligence.