Generating a string of random numbers is easy. The hard part is proving that they’re random. As Dilbert creator Scott Adams once pointed out, “that’s the problem with randomness: you can never be sure ...

To simulate chance occurrences, a computer can’t literally toss a coin or roll a die. Instead, it relies on special numerical recipes for generating strings of shuffled digits that pass for random ...

NIST (the National Institute of Standards and Technology, an agency of the U.S. Department of Commerce, has formally removed Dual_EC_DRBG from its draft guidance on random number generators. This is ...

If you want to start an argument in certain circles, claim to have a random number generation algorithm. Turns out that producing real random numbers is hard, which is why people often turn to strange ...

Randomness can be a Good Thing. If your system generates truly random numbers, it can avoid and withstand network packet collisions just one of many applications. Here's what you need to know about ...

Quantum physics can be exploited to generate true random numbers, which have important roles in many applications, especially in cryptography. Genuine randomness from the measurement of a quantum ...

The United States National Institute of Standards and Technology (NIST) has revised its recommendations for methods used to generate random numbers, and formally removed an algorithm suspected to ...

Researchers propose a True Random Number Generation (TRNG) using dark pixel values of images received from the CMOS image sensor to provide unpredictability to the passwords. “Random Number Generators ...