Parameter-free Streaming Distance-based Outlier Detection

Dealing with anomaly detection in streaming data using distance-based techniques suffers from sensitivity to the input parameters. To solve this problem, we propose a parameterfree self-tuning solution, which can decide optimized parameters on the fly. Our technique achieves better or equal performance with traditional distance-based solutions even when these have been fine-tuned.