The Simplest Of Pseudo Random Number Generators

A truly random number is something that is surprisingly difficult to generate. A typical approach is to generate the required element of chance from a natural and unpredictable source, such as radioactive decay or thermal noise. By contrast it is extremely easy to generate numbers that look random but in fact follow a predictable sequence. A shift register with feedback through an XOR of its output and one of its stages will produce a continuous stream of pseudo-random bits that repeat after a set period.

[KK99] has created the simplest possible pseudo-random binary sequence generator, using a three-bit shift register. It’s realised on a pleasingly retro piece of perfboard, with a CD4047 as clock generator and a 74HC164 shift register doing the work. Unusually the XOR gate is made from discrete transistors, 2N3053s in bulky TO39 packages, and for a particularly old-fashioned look a vintage HP LED display shows the currently generated number. A relatively useless pseudo-random sequence with a period of seven bits is the result, but the point of this circuit is to educate rather than its utility. You can see it in operation in the video below the break.

We had a demonstration of the dangers of using a pseudo-random sequence back in 2016. The German military cipher nicknamed “Tunny” by British codebreakers relied upon a mechanical sequence generator, and the tale of its being cracked led to the development of Colossus, the first stored-program electronic computer.

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Twitter RNG is Powered By Memes

Twitter is kind of a crazy place. World leaders doing verbal battle, hashtags that rise and fall along with the social climate, and a never ending barrage of cat pictures all make for a tumultuous stream of consciousness that runs 24/7. What exactly we’re supposed to do with this information is still up to debate, as Twitter has yet to turn it into a profitable service after over a decade of operation. Still, it’s a grand experiment that offers a rare glimpse into the human hive-mind for anyone brave enough to dive in.

One such explorer is a security researcher who goes by the handle [x0rz]. He’s recently unveiled an experimental new piece of software that grabs Tweets and uses them as a “noise” to mix in with the Linux urandom entropy pool. The end result is a relatively unpredictable and difficult to influence source of random data. While he cautions his software is merely a proof of concept and not meant for high security applications, it’s certainly an interesting approach to introducing humanity-derived chaos into the normally orderly world of your computer’s operating system.

Noise sampling before and after being merged with urandom

This hack is made possible by the fact that Twitter offers a “sample” function in their API, which effectively throws a randomized collection of Tweets at anyone who requests it. There are some caveats here, such as the fact that if multiple clients request a sample at the same time they will both receive the same Tweets. It’s also worth mentioning that some characters are unusually likely to make an appearance due to the nature of Twitter (emoticons, octothorps pound signs, etc), but generally speaking it’s not a terrible way to get some chaotic data on demand.

On its own, [x0rz] found this data to be a good but not great source of entropy. After pulling a 500KB sample, he found it had an entropy of 6.5519 bits per byte (random would be 8). While the Tweets weren’t great on their own, combining the data with the kernel’s entropy pool at /dev/urandom provided something that looked a lot less predictable.

The greatest weakness of using Twitter as a source of entropy is, of course, the nature of Twitter itself. A sufficiently popular hashtag on the rise might be just enough to sink your entropy. It’s even possible (though admittedly unlikely) that enough Twitter spam bots could ruin the sample. But if you’re at the point where you think hinging your entropy pool on a digital fire hose of memes and cat pictures is sufficient, you’re probably not securing any national secrets anyway.

(Editor’s note: The way the Linux entropy pool mixes it together, additional sources can only help, assuming they can’t see the current state of your entropy pool, which Twitter cats most certainly can’t. See article below. Also, this is hilarious.)

We’ve covered some fantastic examples of true random number generators here at Hackaday, and if you’re looking for a good primer for the Kingdom of the Chaotic, check out the piece by our own [Elliot Williams].

[Thanks to DarkSim905 for the tip]

Shift Register Powered Realistic Candle Flicker

[Kevin Darrah] recently went out to dinner at a restaurant that was using some cheap LED candles (yuck) instead of the real thing. And in the true spirit of a hacker, he started to notice the patterns programmed into the fake flame repeat over and over again. And like any hacker might, his mind started to devise a better way.

Now’s the time where some of us lazy hackers might grab a microcontroller, and copy and paste in some pseudo-random number generating code you found on the Internet, but not [Kevin]. The basics of his hack uses two shift registers tied together that are fed a single clock signal, and also a latch signal that is slightly delayed version of the same signal made by a RC-time circuit.

The randomness of the output is created is by feeding back the outputs of the shift registers to an XOR gate. If you want to learn more about this, the technique it’s called a “linear feedback shift register“. It’s commonly used as a poor-man’s random number generator, although it’s not technically truly random, statistically it does a very good job. You can see the results in the video after the break where [Kevin] describes the circuit.  He wraps up the hack with a battery and solar charging circuit as well to make a completed project.

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The Most Random Electronic Dice Yet

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If you’ve written a great library to generate random numbers with a microcontroller, what’s the first thing you would do? Build an electronic pair of dice, of course.

[Walter] created the entropy library for AVRs for a reliable source of true random numbers. It works by using the watchdog timer’s natural jitter; not fast by any means but most sources of entropy aren’t that fast anyway. By sampling a whole lot of AVR chips and doing a few statistical tests, it turns out this library is actually a pretty good source of randomness, at least as good as a pair of dice.

The circuit itself uses two 8×8 LED matrices from Adafruit, an Arduino, and a pair of buttons. The supported modes are 2d6, 2d4, 2d8, 2d10, 1d12, 1d20, a deck of cards, a single hex number, a single 8-bit binary number, or an eight character alphanumeric password. It’s more than enough for D&D or when you really need an unguessable password. Video demo below.

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We’ll take the fries.

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We’ve all been there; hardest decision we’ve ever had to make. College and debt or freedom but no career? Start a family or live out alone? The number 2 with a small shake or side of fries?!

[Leon] sent in his random number generator, oddly enough not to just generate a number, but help us through with those life altering decisions. Using a noise diode like setup he’s able to generate random bits, which an ATtiny24 then converts and displays on a 7 segment LED. His generator also has the ability to set upper and lower limits. Seems like an awful lot of work to avoid the freedom of choice paradox, but we enjoyed the project none the less. Check out a video after the break. Continue reading “We’ll take the fries.”