This study is going to investigate purposefully the role being played by machine learning algorithms that particularly target cyber-security threats when using classifiers such as random forests and decision trees to filter the dataset. The research involves utilizing data of attack types which leads to the high accuracy of calculations that would be able to scale due to the output. The application of these algorithms can progress cyberspace security due to their capabilities in modern threat landscape.

Machine learning, cybersecurity, threat detection, Random Forest, Decision Trees, dataset analysis, cyber-attacks, accuracy, scalability, cybersecurity practices.