Efficient Application Identification and the Temporal and Spatial Stability of Classification Schema
Source: University of Cambridge
Motivated by the importance of accurate identification for a range of applications, this paper compares and contrasts the effective and efficient classification of network-based applications using behavioral observations of network-traffic and those using Deep-Packet Inspection. Importantly, throughout the authors' paper, they are able to make comparison with data possessing an accurate, independently-determined ground-truth that describes the actual applications causing the network-traffic observed. In a unique study in both the spatial-domain: comparing across different network-locations and in the temporal-domain: comparing across a number of years of data, they illustrate the decay in classification accuracy across a range of application-classification mechanisms.