Table 4 Comparison of Machine learning and deep learning

Network Feature

Features extraction is required from the raw data to conduct a classification.

Features extraction is not necessary and the raw data could be used in a completely autonomous to build IDS.

Number of Contents

Only a part of available data is being utilized for building IDS. The data is scaled into a small vector of features, e.g. statistical correlations, it isinevitably throwing away most of the data

Processes all of the data, with a large number of features to detect the intrusions.

Correlations

Features selected by a human domain expert

Using raw data offers the capability to discover non-linear correlations between data that are too complex for a human expert.