Computer networks have become an essential component of the infrastructure of modern institutions, particularly healthcare organizations that rely on exchanging data and information between medical devices, servers, and electronic systems. With the increasing frequency and complexity of cyberattacks, the need for more advanced security solutions has become evident. Artificial intelligence is among the leading technologies contributing to enhanced network security. Artificial intelligence relies on algorithms capable of analyzing large volumes of data and identifying patterns and behaviors. This enables the detection of unusual network activities that may indicate an attempted intrusion or cyberattack. For example, machine learning models can be trained using network traffic data to identify normal behavior and subsequently detect unusual changes. Applications of artificial intelligence in network security include detecting denial-of-service attacks, identifying unauthorized access attempts, analyzing malware, and continuously monitoring network traffic. Deep learning techniques can also be used to analyze complex patterns that may be difficult to identify using traditional security systems. In healthcare institutions, these technologies are particularly important because they help protect networks connecting medical imaging devices, laboratories, and patient management systems. They also reduce the risk of healthcare data theft or manipulation. Despite their significant advantages, the effectiveness of these technologies depends on the quality of training data, continuous model updates, and the reduction of false security alerts. Therefore, artificial intelligence represents an important tool in developing network security systems by shifting from traditional protection methods toward more advanced systems capable of predicting, detecting, and responding to cyber threats. Al-Mustaqbal University is the first one university in Iraq.