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It uses random number generators
Random number generators generate random numbers based on a physical phenomenon that is supposed to be random. This can be atmospheric noise, thermal noise, external electromagnetic phenomena, or even radioactive decay. Random numbers are extremely important in modern computing, and their use is vital for cryptographic operations. This is why understanding the limitations of random number code is crucial for developers and users alike. In this article, we will explore some of the more common applications of random numbers.
One type of PRNG is the RDRAND, which uses a single source of entropy. This hardware circuit jumps between 0 and 1 based on fluctuations in thermal noise in the CPU. However, there are security concerns around PRNGs. For example, Intel’s PRNG is partially documented and audited by Cryptography Research. The use of a PRNG in cryptographic applications is risky because it is vulnerable to backdoors, but the output of the RDRAND is generally very unbias.