If you're comparing sample-for-sample, maybe. But that's not what is performed by music identification algorithms - it would be both slow (to the point of being

If you're comparing sample-for-sample, maybe. But that's not what is performed by music identification algorithms - it would be both slow (to the point of being unusable) and inaccurate (because of re-encoding, etc). Instead they rely on different kinds of dimensionality reduction that match the way we perceive music, so they only compare smaller amounts of data to get more perceptually relevant matches. The Shazam fingerprinting algorithm is the best known but there are others. So if you submit white noise to a copyright database, it could match different white noise recordings.