Rights protection of trajectory datasets

This work presents a technique of convincingly claiming ownership rights over a trajectory dataset. The presented methodology distorts imperceptibly a collection of sequences, effectively embedding a secret key, while retaining as well as possible the neighborhood of each object, which is vital for operations such as similarity search, classification or clustering.