Machine Learning for Side Channel Attacks
This is a quirky one, but it’s kind of “flag-planting” in the ML/Security world. For years, security researchers have spent time finding what they call “side-channel” attacks. An example is, say, listening to the soup that someone makes when typing, and from that sound, working out what they are typing. It’s called “side-channel” because it’s not, say, capturing the keystrokes via the computer, it’s via an additional “channel”.
The main point of this paper is that they’re applying standard ML techniques, in particular in regards to voltage, and are able to make an estimate of which applications are running on a given piece of hardware. This might not sound super useful as it is, but, as always in the security world, there’s much more juice to be squeezed here.
This will definitely be a space to watch in the security space - bringing in AI techniques to enhance our offensive security capabilities!
