An Exploration of Data Mining and Machine Learning Methods
Data mining is the process of sorting through large data sets to identify patterns and establish relationships to solve problems through data analysis.
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
Machine learning is an application of artificial intelligence (AI) that provides systems the ability to automatically learn and improve from experience without being explicitly programmed.
The wired networks prove to have more layers of defense at firewalls, operating systems and networks. This makes them less vulnerable to attacks than wireless networks, but still a target for cybersecurity issues.
Methods of data mining and machine learning are very complex and pose challenges for understanding when and how each should be used. The complexity of algorithms also make it harder to tell which method will be most effective when dealing with cybersecurity attacks.
When determining the effectiveness of the methods, there are many criteria that must be taken into account. They include accuracy, complexity, time for classifying an unknown instance with a trained model, and understandability of the final solution of each machine learning or data mining method.
There are three types of cyber analysis that work with an intrusion detection system: misuse-based, anomaly-based, and hybrid. Misuse-based are used to detect known attacks based on the signatures of those types of attacks. Anomaly-based techniques identify anomalies in normal behavior and can detect zero-day attacks. Hybrid techniques combine misuse and anomaly detection. They can detect both known and unknown attacks while having a small false positive rate.
Methods of data mining and machine learning are very complex and pose challenges for understanding when and how each should be used. The complexity of algorithms also make it harder to tell which method will be most effective when dealing with cybersecurity attacks.
When determining the effectiveness of the methods, there are many criteria that must be taken into account. They include accuracy, complexity, time for classifying an unknown instance with a trained model, and understandability of the final solution of each machine learning or data mining method.
There are three types of cyber analysis that work with an intrusion detection system: misuse-based, anomaly-based, and hybrid. Misuse-based are used to detect known attacks based on the signatures of those types of attacks. Anomaly-based techniques identify anomalies in normal behavior and can detect zero-day attacks. Hybrid techniques combine misuse and anomaly detection. They can detect both known and unknown attacks while having a small false positive rate.
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