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Comment by cbhl | Hacker News Reader

@kevincennis: A counter-argument to that is that an attacker could run shazam/soundcloud to fingerprint the music, and then subtract the music from the recorded signal. It would be more work, certainly, but I don't think e.g. just playing the radio would be enough to mask the side-channel.

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Filtering out a signal that's in the same band is notoriously difficult.

If the signal you're subtracting is known to you, you can simply lock the phases and subtract. That's pretty trivial.

But knowing the name of the song doesn't necessarily give you a known signal to subtract. Conceivably, you could be working with a version of the song that was compressed differently than the one playing on the target computer. In which case, the two signals might not have the same waveform, and they wouldn't cancel.

To the listener's ear, the signals may sound identical. A good example of this principle is musical instruments. Have a skilled violinist play the same note twice with the same articulation for the same duration under the same conditions. Record each sample the same way. Most listeners would say these two samples are identical. But if you invert one and then mix them, they won't cancel, because they didn't actually have the same waveform.

But it's definitely an interesting approach, and potentially viable, if a good filtering algorithm can be worked out. My suspicion is that such an algorithm exists or is at least possible. But I'm not an audio engineer, so I'm not certain.

I suspect that, in practice, playing music will provide enough of a barrier to mitigate attacks using these side-channels. But then again, in practice, I'd hope that attacks using these side-channels are pretty infrequent to begin with.

Besides, in practice, upgrading to GnuPG 1.4.16 (released today) is supposed to also mitigate the key extraction attack using this side channel.

The naive approach I suggested would be easily defeated by playing two songs from two different sources; which itself would be defeated by setting up soundcloud on two devices in both places and carefully setting up/analyzing/modelling the room so that you can adjust the signal you're subtracting to account for the distance the sound waves travel and whatnot. I think after a while you just get increasing complexity and diminishing returns -- i.e. it becomes an arms race.

Certainly you also can't assume that a recording of a sound played via crappy laptop speakers will even closely resemble the original waveform. Playing back (distortion by differing air pressure etc) and recording (environment & A/D noise anyone?) will completely distort it.

That's a really interesting point. I hadn't thought about phase cancellation at all. You certainly couldn't remove everything, since the signal you picked up would be influenced by the speakers/room/microphone/converters/etc, but you still might be able to remove a significant portion of the music that way.

I believe this would only mask the direct sound waves, not the reflections caused by the room. Perhaps masking the direct sound is enough, but maybe not if the reflections have sufficient energy.

If you've got enough information to cancel the main signal, then you've also got enough information to cancel the reflections. It will take a more computational power though, which is okay if you're doing the analysis on a recording.

The brute force way is to do an exhaustive search, repeatedly correlating the signal you are looking to cancel and the received signal, whilst "sliding" the known signal across the received signal, which means adding a delay to the known signal between each correlation. Correlation peaks can be picked out and used to cancel the reflections. Similar techniques are regularly used in radio communications, to combat multipath fading, which is a fancy way of saying that the received radio signal contains reflections.

Edit: remove cruft at end of comment.

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