Abstract

Cybersecurity aggregates are numerical data obtained by aggregation on features along a database of cybersecurity reports. These aggregates are obtained by integration of time-stamped tables using some recent results of non-standard calculus. Time-series of aggregates are shown to contain relevant information about the concrete system dealt with. Trend time series is also forecasted using known data-driven methods. Although absolute forecasting of trend time series is not obtained, a directional forecasting of trend time series is achieved thence validated by means of a rolling cross validation scheme on a public database of Scareware reports.