Analysis of Internet Measurement Systems for Optimized Anomaly Detection System Design

Abstract

Although there exist very accurate hardware systems for measuring traffic on the internet, their widespread use for analysis tasks is limited by their high cost. On the other hand, less expensive, software-based systems exist that are widely available and can be used to perform a number of simple analysis tasks. The caveat with using such software systems is that application of standard analysis methods cannot proceed blindly because inherent distortions exist in the measurements obtained from software systems. The goal of this paper is to analyze common Internet measurement systems to discover the effect of these distortions on common analysis tasks. Then by selecting one specific task, periodic signal detection, a more in-depth analysis is conducted which derives a signal representation to capture the salient features of the measurement and develops a periodic detection mechanism designed for the measurement system which outperforms an existing detection method not optimized for the measurement system. Finally, through experiments the importance of understanding the relationship between the input traffic, measurement system configuration and detection method performance is emphasized.