5 ms·
A pretty meaningless article. It seems that they want to generate random numbers (to use as keys) with biological processes (instead of physical ones, like nois
by mdpopescu 8y ago
A pretty meaningless article. It seems that they want to generate random numbers (to use as keys) with biological processes (instead of physical ones, like noise generators). It would be cheaper to have minimum-wage workers throw dice and record the results...
- nickpsecurity 8y agoI agree it's pretty meaningless as cheap TRNG's are a solved problem. Far as dice, one of my experiments in TRNG's was a shoe box full of dice. Shake it up, dump them, put the numbers into a computer program, whiten it, and tada. The first one used 8-sided die since each one maps cleanly to 3 bits (2 ^ 3 = 8). The next iteraiton used regular, 6-sided die just discarding any above four to map easily to 2 bits. Did something similar with a deck of cards after throughout shuffling. Such methods were good for producing an initial secret that I'd use with algorithms like CPRNG's to produce the rest.
- zokier 8y ago> Did something similar with a deck of cards after throughout shuffling. I was under the impression that shuffled card deck is more difficult to convert to random number, you need something like Lehmer Code. Did you find some easy good shortcut here?
- nickpsecurity 8y agoIf you use 32 cards, it maps cleanly to 5-bits of entropy. You can keep the others in there to keep shuffling randomness of 52 cards. Just ignore them when entering numbers.
- klodolph 8y agoUsing 32 cards to get 5 bits of entropy only works if you are randomly selecting a single card at a time. If you shuffle a deck of 32 cards, you get ~117 bits, a fair bit less that the 160 bits you would get for 5 bits/card, and there's extra math.
- nickpsecurity 8y agoI shuffled a full deck multiple times, no less than five, before using cards in order ignoring any but the 32. I know shuffling all the cards adds randomness vs just shuffling 32. I do want to know why you say two things: 1. 32 = 117 bits of entropy, not 150, after lots of shuffling. 2. It works if I randomly select a single card at a time but not in order from a randomized deck. In order from a randomized deck should give the entropy amount or close to it. I'm not a probability expert. Just doing what I could with good, shuffling skills. Good enough that people refused to play Spades with decks I shuffled. So, I thought I had good entropy. I'm always up for improvements.
- klodolph 8y agoThe first card you draw can be any one of 32 cards. This gives you 5 bits of entropy. The second card can be any one of 31 cards, because it can't be the same as the first card. This gives you log2 31 = ~4.95 bits of entropy. If this argument isn’t convincing, think of it this way. If you draw two cards, then there are 32 choose 2 cards you can draw, and 32 choose 2 is 496, giving log2(496) = ~8.95 bits. You can draw them in two different orders, giving 1 extra bit, total of ~9.95. If you could draw a pair of the same card, there are 32 different pairs to draw, giving (496 * 2) + 32 possibilities, which is 1024, and log2 1024 = 10. But you can't draw a pair of the same card. Or for another argument, consider that there are 32! different ways to shuffle the deck with 32 cards. log2 32! = ~117.
- gregmac 8y agoThe paper doesn't seem to acknowledge existence of TRNG's, let alone compare results to them. Compared to pseudo-random generators, this is an improvement, but compared to existing hardware random number generator chips -- which are available on the market for tens of cents -- is this cheaper? Higher entropy? Faster? Easier to implement? It's great to do research like this as that is how we get advancements and breakthroughs, but it's another thing to completely ignore an entire sub-field of the area you're researching in order to misrepresent what you're doing as being an amazing breakthrough. All it would have taken is a simple statement like "We acknowledge there are existing non-pseudo-random solutions to this problem that use thermal noise, radioactive decay, etc, but wanted to try a biological process because ____________".
- zokier 8y ago> existing hardware random number generator chips -- which are available on the market for tens of cents Bit of a tangent but do you have any particular devices in mind? I did a cursory search, and found only Microchip (nee Atmel) ATSHA204A and the related family of products, but those are full-blown fat crypto processors. Are there some cheaper/simpler plain TRNG chips available somewhere?