Predictive Modelling for Network Threat Detection Using Artificial Intelligence Techniques

The advent of artificial intelligence (AI) techniques has revolutionized network security by enabling predictive modelling for threat detection. This abstract proposes a novel approach to enhancing network security through predictive modelling, leveraging advanced AI techniques. By analyzing vast amounts of network traffic data, AI algorithms can identify patterns indicative of potential threats, including malware, intrusions, and anomalous activities. The predictive models developed through this approach can forecast potential network vulnerabilities and pre-emptively detect emerging threats before they manifest into security breaches. This proactive stance empowers organizations to fortify their network defenses, minimize the risk of cyberattacks, and safeguard sensitive information. Through the fusion of AI and predictive modelling, this research endeavors to pave the way for more robust and resilient network security frameworks in an increasingly interconnected digital landscape.