What Type of Random Number Generator is Used in the Casino Gaming Industry? [closed]

Answer 1

Casinos shouldn't be using Pseudo-random number generators, they should be using hardware ones: http://en.wikipedia.org/wiki/Hardware_random_number_generator

Answer 2

I for sure have seen a german gambling machine that was not allowed to be ran commercially after a given date, so I suppose it was a PNRG with a looong one time pad seed list.

Answer 3

If you want to do it properly you have to get physical - ERNIE the UK national savings number picker uses a shot noise in Neon tubes.

Answer 4

Most poker sites use hardware random number generators. They will also modify the output to remove any scaling bias and often use 'pots' of numbers which can be 'stirred' using entropic events (user activity, serer i/o events etc). Quite often the resultant numbers just index pre-generated decks (starting off as a sorted list of cards).

Answer 5

There are many things that the gaming sites have to consider when choosing/implementing an RNG. Without due dilligence, it can go spectacularly wrong.

To get a licence to operate a gaming site in a particular jurisdiction usually requires that the RNG has been certified by an independent third-party. The third-party testers will analyse the source code and run statistical tests (e.g. Diehard) to ensure that the RNG behaves randomly. Reputable poker sites will usually include details of the certification that their RNG has undergone (for example: PokerStars's RNG page).

I've been involved in a few gaming projects, and for one of them I had to design and implement the RNG part, so I had to investigate all of these issues. Most poker sites will use some hardware device for entropy, but they won't rely on just hardware. Usually it will be used in conjunction with a pseudo-RNG (PRNG). There are two main reasons for this. Firstly, the hardware is slow, it can only extract a certain number of bits of entropy in a given time period from whatever physical process it is monitoring. Secondly, hardware fails in unpredictable ways that software PRNGs do not.

Fortuna is the state of the art in terms of cryptographically strong PRNGs. It can be fed entropy from one or more external sources (e.g. a hardware RNG) and is resilient in the face of attempted exploits or RNG hardware failure. It's a decent choice for gaming sites, though some might argue it is overkill.

Pokerroom.com used to just use Java's SecureRandom (they probably still do, but I couldn't find details on their site). This is mostly good enough, but it does suffer from the degrees of freedom problem.

Most stock RNG implementations (e.g. Mersenne Twister) do not have sufficient degrees of freedom to be able to generate every possible shuffle of a 52-card deck from a given initial state (this is something I tried to explain in a previous blog post).

EDIT: I've answered mostly in relation to online poker rooms and casinos, but the same considerations apply to physical video poker and video slots machines in real world casinos.

Answer 6

You probably need a cryptographically secure pseudo-random generator. There are a lot of variants. Google "Blum-Blum-Shub", for example.

The security properties of these pseudo-random generators will generally be that, even when the attacker can observe polynomially many outputs from such generators, it won't be feasible to guess the next output with a probability much better than random guessing. Also, it is not feasible to distinguish the output of such generators from truly random bits. The security holds even when all the algorithms and parameters are known by the attacker (except for the secret seed).

The security of the generators is often measured with respect to a security parameter. In the case of BBS, it is the size of the modulus. This is no different from other crypto stuff. For example, RSA is secure only when the key is long enough.

Note that, the output of such generators may not be uniform (in fact, can be far away from uniform in statistical sense). But since no one can distinguish the two distributions without infinite computing power, these generators will suffice in most applications that require truly random bits.

Bear in mind, however, that these cryptographically secure pseudo-random generators are usually slow. So if speed is indeed a concern, less rigorous approaches may be more relevant, such as using hash functions, as suggested by Jeff.