A random number generator using biological populations as entropy sources

Imagine you are trying to pick a lock, but the key you need is a number so truly random that no one, not even a supercomputer, could ever guess it. This is the world of cryptography, where "True Random Number Generators" (TRNGs) are the guardians of our digital secrets. Usually, these guardians rely on the jittery, unpredictable dance of electrons in a wire or the static hiss of a radio to create their numbers. But what if we could borrow that unpredictability from something alive? Think of a crowd of people in a room; if you try to predict exactly where every single person will step next second, it's impossible because everyone is moving for their own reasons. Scientists have long wondered if we could use that kind of chaotic, living movement to generate numbers that are even harder to crack than the usual electronic noise.

This is exactly what Hiroshi Yoshida from Kyushu University explored in a short report published in July 2026. The paper proposes a wild new way to make random numbers: by listening to the squirming, wiggling movements of insect larvae. Instead of just measuring electronic noise, the researchers put a bunch of larvae (like phoenix worms or mealworms) into a container with metal wires sticking into them. As the larvae crawl over the wires, they change the electrical resistance in a messy, unpredictable way. The researchers turned these resistance changes into a buzzing signal, sampled it, and used a special math trick called "XOR" to mix the signals together. The result? A stream of numbers that passed some of the strictest tests for randomness in the world, suggesting that a container of wiggly bugs might just be a surprisingly tough-to-predict source of security.

The Bug-in-a-Box Generator

So, how does a box of bugs become a computer's best friend? Imagine you have a jar filled with hundreds of tiny, wriggling larvae. Now, stick two metal wires into the jar so they are touching the squirming mass. In the world of electronics, when these bugs crawl over the wires, they act like tiny, moving bridges. Sometimes a bug touches both wires, lowering the resistance; sometimes it moves away, raising it. Because the bugs are alive and moving in ways that are impossible to predict or model, the electrical resistance between the wires is constantly fluctuating in a chaotic dance.

The researchers took this messy electrical signal and fed it into a circuit called an "oscillator." Think of an oscillator like a metronome that keeps time. Usually, a metronome ticks at a steady rate. But in this case, the "metronome" is being pushed by the bugs. As the resistance changes, the speed of the ticking (the frequency) speeds up and slows down wildly. The circuit turns these speed changes into a square-wave signal—a digital on/off pattern that is as messy as the bugs themselves.

To get a random number, the researchers simply "took a snapshot" of this signal at a specific speed. If they took the snapshot too fast, they might just see the same pattern over and over. But if they sampled it at a speed slower than the signal's fastest tick (specifically, less than 1/10th of the oscillation frequency), the result was a string of 0s and 1s that looked completely random.

The Magic of Mixing (XOR)

One of the smartest parts of this design is how the researchers handled the fact that one jar of bugs might not be perfect. Maybe the bugs in one corner are sleeping, or maybe the wires are a bit sticky. To fix this, they didn't just rely on one pair of wires. In their "extended" setup, they used six wires in the same jar (or even separate jars) to create six different signals.

They then used a logic gate called "XOR" (Exclusive OR) to mix these signals. You can think of XOR like a game of "odd one out" or a magical blender. If you have two signals that are both a little bit biased (maybe one has too many 0s and the other has too many 1s), mixing them together with XOR tends to cancel out those biases. It's like if you have a cup of water that is too salty and a cup that is too sweet; mixing them might give you a perfectly balanced drink. The paper notes that this method has a superpower: even if one of the bug-sources fails or gets predictable, as long as the others are still "healthy" and chaotic, the final mix remains safe and random. This makes the system much more reliable than relying on a single source of entropy.

Did the Bugs Pass the Test?

The researchers put their bug-powered generator through the wringer with some very strict tests, including the NIST SP 800-90B and SP 800-22, which are the gold standards for checking if a random number generator is actually random.

Here is what they found:

• The Raw Signal: When they tested the raw numbers coming straight from the bugs without any extra processing, the results were a bit mixed. At lower sampling speeds (like 3 kHz or 5 kHz), the numbers passed some basic tests but failed the stricter ones. For example, at a sampling frequency of 111 kHz, the raw data failed the tests completely.
• The Secret Sauce (SHA-256): The paper suggests that to get truly usable, high-quality random numbers, they needed to run the raw data through a "post-processing" step using a cryptographic hash function called SHA-256. Think of this as a final polish or a sieve that scrubs away any remaining patterns or biases.
• The Result: Once they applied SHA-256, the numbers became much stronger. In the tests, the "minimum entropy per byte" (a measure of how unpredictable the data is) jumped to 7.5 or higher in several cases, well above the 6.4 threshold needed to be considered practical for real-world use. Even the tricky 111 kHz sampling rate, which failed before, passed all the tests after this polishing step.

Why This Matters

The main takeaway from this study is that the chaotic, collective movement of living organisms is a surprisingly robust source of randomness. Unlike electronic noise, which can sometimes be modeled or predicted by physics equations, the behavior of a swarm of larvae is incredibly difficult to forecast. The paper suggests that this biological approach could be harder for hackers to predict or manipulate than traditional electronic methods.

However, the authors are careful not to claim this is a finished product ready for your smartphone. They note that the system works best when combined with cryptographic post-processing like SHA-256. They also suggest that future work could look at how different species of bugs or different densities of larvae might change the quality of the randomness. For now, this research offers a fascinating glimpse into a future where our digital security might just be powered by a jar of wiggling worms, proving that sometimes, the most unpredictable things in the universe are the ones that are alive.