The Role of Machine Learning in Cyber Security

Cyber security is like a moving target—hackers are always coming up with new tricks, so systems that just look for “known” issues can’t keep up anymore. That’s where machine learning (ML) comes in. Instead of following fixed rules, ML looks for anything unusual or suspicious in huge amounts of data. This means it can spot new types of threats much faster than traditional methods. In this paper, we explore how ML is being used for things like catching malware, stopping phishing attacks, and detecting intrusions in networks. We also talk about the tough parts, like needing lots of good data, powerful computers, and making sure attackers don’t fool the ML systems. Our results show that while ML is a big help, it’s not a silver bullet. The best protection happens when ML works together with traditional security tools and the know-how of human experts.