Adaptive Anomaly Detection on Network Data Streams
Elizabeth Riddle-Workman, Marina Evangelou, Niall M. Adams · 2018
As the number of cyber-attacks increases, there has been increasing emphasis on developing complementary methods of detection to the existing signature-based approaches. This work builds upon a previously discovered persistent structure within the Los Alamos National Laboratory network data sources, to develop a regression based streaming anomaly detection mechanism that can adapt to the network behaviour over time. The methodology has also been applied to a new data set of the same network to assess the extent of its pertinence in time.