Correlating Machine Learning Confidence to Outlier Detection for Network Monitoring Tasks
University of Würzburg, (November 2023)Zusammenfassung
The detection of outliers in network traffic is an omnipresent topic for network security, e.g., to detect malicious activity or unknown devices and apps in the network, that deviate from the normal network activity. The goal of this thesis is to compare a myriad of different detection algorithms and compare them not only regarding their accuracy and detection time, but also with regards to the false negatives and false positives, i.e., investigate the outliers they disagreed on, which were falsely detected etc., as this may be a reason to include more than one algorithm, e.g., in a monitoring system. For more information, read the linked presentation slide and/or message katharina.dietz@uni-wuerzburg.de.