MalPaCA: Malware behaviour analysis using unsupervised machine learning: Comparative analysis of various clustering algorithms on determining the best performance in terms of network behaviour discovery

MalPaCA makes use of unsupervised machine learning to provide malware capability assessment by clustering the temporal behaviour of malware network packet traces. A comparative analysis was performed on various clustering algorithms to determine the best clustering algorithm in terms of network behaviour discovery. The clustering algorithms...

Accelerating Cluster Assignment for SeqClu

Clustering is a group of (unsupervised) machine learning algorithms used to categorize data into clusters. The most popular clustering algorithm is k-means clustering. K-means clustering clusters the data into k clusters where a cluster is represented by the mean of the data points called a centroid. Instead of using the mean as a centroid, a...