Frequently, port scans are early indicators of more serious attacks. Unfortunately, the detection of slow port scans in company networks is challenging due to the massive amount of network data. This paper proposes an innovative approach for preprocessing flow-based data which is specifically tailored to the detection of slow port scans. The preprocessing chain generates new objects based on flow-based data aggregated over time windows while taking domain knowledge as well as additional knowledge about the network structure into account. The computed objects are used as input for the further analysis. Based on these objects, we propose two different approaches for detection of slow port scans. One approach is unsupervised and uses sequential hypothesis testing whereas the other approach is supervised and uses classification algorithms. We compare both approaches with existing port scan detection algorithms on the flow-based CIDDS-001 data set. Experiments indicate that the proposed approaches achieve better detection rates and exhibit less false alarms than similar algorithms.

We demonstrate that pearling droplets will be released from droplets as they sliding down a partially wetting glass plate excited by Lamb waves. During the movement, we find that the transitions at generating pearling are independent of the drop size and depend only on a critical capillary number Ca. Further up, the position of the pearls must be at or around the droplet’s advancing or receding end of the initial state.

The kinetics of the charge transport across the solid-liquid interface between the electrode and the electrolyte is controlled by a diffusion boundary layer, which is responsible for the time needed for charging the battery. Therefore a removal of this boundary layer by acoustic streaming induced by surface acoustic waves propagating on the electrodes was considered to be promising approach for a reduction of the charging time. Previous electropolishing experiments have shown that Scholte waves were particularly effective in that respect. This concept has been transferred to a model electrode system representing the core of a lead acid battery, where significant reductions of the charging time and corresponding increases of the charging currents resulting from surface acoustic wave sonication have been observed.