[Jason Dookeran] reminded us of something we don’t like to think about. Your printer probably adds barely noticeable dots to everything you print. It does it on purpose, so that if you print something naughty, the good guys can figure out what printer it came from. This is the machine identification code and it has been around since the days that the US government feared that color copiers would allow wholesale counterfiting.

The technology dates back to Xerox and Canon devices from the mid-80s, but it was only publicly acknowledged in 2004. With color printers, the MIC — machine identification code — is a series of tiny yellow dots. Typically, each dock is about 10 microns across and spaced about a millimeter from each other. The pattern prints all over the page so that even a fragment of, say, a ransom note can be identified.

Apparently, printers use different encoding schemes, but reading the dots is usually done by scanning them under a blue light.

The EFF has an out-of-date list that identifies many printers that track. But they point out that some printers may use a different method, especially those that can’t print yellow. They also mention that it is likely that “all recent commercial color laser printers” print some kind of code.

If you want to check your printer, [Jason] points out an Instructable and a website that can decode common patterns.

While we can think of times we are glad people can figure out the origin of a death threat or a ransom note, we can also think of times when we would like whistleblowers or people with different opinions to be able to print things without fear of retribution. But either way, the technology is an interesting real-world example of steganography.

We prefer these yellow dots. Yellow steganography reminds us of turmeric.

Title image: “Yellow dots produced by an HP Color LaserJet CP1515n” CC BY-SA 3.0 by [Ianusisu].

The radio hackers in the audience will be familiar with a spectrogram display, but for the uninitiated, it’s basically a visual representation of how a range of frequencies are changing with time. Usually such a display is used to identify a clear transmission in a sea of noise, but with the right software, it’s possible to generate a signal that shows up as text or an image when viewed as a spectrogram. Musicians even occasionally use the technique to hide images in their songs. Unfortunately, the audio side of such a trick generally sounds like gibberish to human ears.

Or at least, it used to. Students from the University of Michigan have found a way to use diffusion models to not only create a spectrogram image for a given prompt, but to do it with audio that actually makes sense given what the image shows. So for example if you asked for a spectrogram of a race car, you might get an audio track that sounds like a revving engine.

The first step of the technique is easy enough — two separate pre-trained models are used, Stable Diffusion to create the image, and Auffusion4 to produce the audio. The results are then combined via weighted average, and enter into an iterative denoising process to refine the end result. Normally the process produces a grayscale image, but as the paper explains, a third model can be kicked in to produce a more visually pleasing result without impacting the audio itself.

Ultimately, neither the visual nor audio component is perfect. But they both get close enough that you get the idea, and that alone is pretty impressive. We won’t hazard to guess what practical applications exist for this technique, but the paper does hint at some potential use for steganography. Perhaps something to keep in mind the next time we try to hide data in an episode of the Hackaday Podcast.