What Is a Random Number Generator and How Does It Work? 

Thomas Burger
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The word “random number generator” is commonly heard these days, particularly among those who gamble online. However, random number generators, sometimes known as RNGs, can be used in a variety of applications other than the gaming sector. They have applications that range from computer games to encryption. Computer simulations, random design, and statistical sampling all rely on the usage of random numbers to succeed. When you choose “shuffle” on a music app, the software employs a pseudo-random number generator. Of course, it’s not fully random because there are limits to how many times a song may be played in a row without skipping another song in the playlist. There would be no such thing in a random generation, and it would be able to play the same music not once, but twice, or even three times in a row. So, how does something like a random number generator work? 

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A random number generator is defined as follows 

A random number generator, or RNG for short, is a piece of software that generates a random sequence of arbitrary symbols such as numbers or letters. To achieve this purpose, several ways can be used, including the computer method, the physical method, the use of a probability distribution, and even the use of humans. The final option is not particularly reliable and is not used very often. The computational method entails running a program to generate a series of numerical values. A physical technique, on the other hand, is more open to interpretation, and it may mean anything from using a regular pair of dice to achieve randomization to using radioactive decay to accomplish the same thing. The act of tossing a coin also qualifies as the generation of random numbers. 

Do Random Number Generators Produce Genuinely Random Numbers? 

A completely random number generator does not exist. It has been demonstrated that creating random results is exceedingly difficult and practically impossible if no natural mechanism is used. RNGs generated by humans can be cracked and predicted because all that is required is the discovery of the rules that generate the sequence. On the other hand, no matter how much computing power you have available, forecasting the waves generated by a storm on an open body of water is extremely impossible. This raises the cost tremendously, making the creation of a true genuinely random number generator significantly more difficult. As a result, we use not one but two types of random number generators: pseudo-random number generators and hardware random number generators, also known as real random number generators (TRNG). 

Generators of Pseudo-Random Numbers 

Pseudo-random number generators are often bits of software designed to generate complicated sequences that appear to be random. The resulting sequences, on the other hand, aren’t truly random because they’re generated by an algorithm. The software that generates them runs within a set of settings, each of which can be discovered and exploited. When given enough data, specialized software can deduce the algorithm that drives the process and then uses that method to their benefit. The trick is to make it impossible or so difficult to comprehend that it isn’t even worth the effort. They are widely used, particularly in the gaming sector, which places less emphasis on the quality of the randomness they generate. When it comes to the outcome of a video game, for example, it makes little difference whether an event was triggered by a truly random sequence or a pseudo-random one. More complex technologies, on the other hand, are necessary for more critical applications such as cryptography. 

Generators of True Random Numbers 

Pseudo random number generators are unsuitable for use in sensitive industries such as cryptography due to their inherent flaws. Any pseudo RNG can be broken given enough time and computing power. True random number generators, also known as hardware random number generators, are used by security agencies to ensure that critical information does not get into the hands of those who would harm the country (HRNG). HRNGs use a random property of some physical object to generate seed tokens, which are subsequently used to generate random sequences. The ensuing sequence is completely random, and it is impossible to predict or exploit it because it is based on an unpredictable event in the actual world. Radioactive decay is consistently recognized as one of the most popular ways. We have no way of knowing when the decay will occur, thus it is a purely random occurrence, according to quantum theory. Using it as a seed, a computer can generate a completely random sequence that is exceedingly difficult, if not impossible, to crack. 


Entropy is the seed that many HRNGs employ in their daily operations. Your computer may keep track of when you clicked the mouse and then use that information, together with a timestamp, to generate a truly random seed. Even if you can’t predict when that time will come, a possible foe has a limited chance of succeeding. This is the method that Linux use for increased cryptographic protection. 


In the current climate, random number generators are becoming an increasingly crucial instrument for defending ourselves against unfair attacks. On the other hand, they can be put to a variety of other uses, some of which are potentially dangerous. The most prominent illustration of this is RdRand, a random number generator that is native to Intel central processing units (CPUs). The contents of RDRand are only known to a select few engineers and scientists working with Intel, and the product’s whole set of specs has never been made available to the general public. This is done out of safety concerns. A few years ago, rumors started to spread that Intel had conspired with the NSA to install a backdoor in RdRand without the company’s knowledge. This was said to have occurred without Intel’s knowledge. The National Security Agency (NSA) was able to decipher any encryption that users of RdRand had built since it had access to the seed tokens. Although it was never established that the assertions were accurate, several key players, including the developers of FreeBSD, have now removed support for RdRand from the products they offer.