In Cryptography What are the advantages of using a PRNG over

In Cryptography, What are the advantages of using a PRNG over an RNG? What are the advantages of using an RNG over a PRNG?

Solution

Solution :

Before beginning to mention the advantages of using PRNG over an RNG in Cryptography, we will first try to understand what Cryptography actually is.

As most of the people are now using internet and other forms of electronic communications, so to protect them from any kind of threat, the electronic security is also becoming more and more important.

Hence, Cryprography is used to protect such types of informations such as , important password and user ids, e-mail messages, credit card and bank details and other such types of imprtant corporate data.

So, Cryptography is a technique to protect these important data and informations by transforming them or to say encrypting them into unreadable format which are also referred to as cypher text and those authorised personel who posses the secret key can decipher it into plain readable text.

Now ,PRNG or Pseudo Random Number Generator and RNG or Random Number Generator, are the two techniques that can be used in Cryptography.

We will study both of them one by one as below,

PRNG or Pseudo Random Number Generator :

a PRNG is a cryptographic alogorithm used to generate numbers that must appear as random.

A PRNG has a secret state. Upon request, it must generate outputs that are indistinguishable from random numbers to an attacker who does not know and cannot guess the secret state.In this way it is very much similar to the stream cipher.

Also, a PRNG must be able to alter its secret state by processing input values that may be unpredictable to an attacker, and must process many inputs to reach a secure state.

Note that the inputs are intended to carry some unknown (to an attacker) information in the PRNG. These are the value typically collected from the physical processes (Like hard drive latencies), user interaction with the machines, or other external, hard-to-predict processes. Typically, system implementers and designers will try to ensure that there is sufficient entropy in these inputs to make them unguessable to any practicle attacker.

So, in simple terms,

PRNGs or Pseudo Random Number Generator , is defined as having appearance of randomness, but nevertheless exhibit a specific, repeatable pattern. The most common type of random number generator, PRNGs are designed to look as random as TRNG (True Random Number Generators), but can be implemented in deterministic software because the state and transition function can be predicted completely.

RNG (Random Number Generator) or TRNG (True Random Number generator):

Truely random is defined as exhibiting true randomness, such as the time between \"tics\" from a Gieger counter exposed to a radioactive element. This type uses a physical source of randomness to provide truely unpredictable numbers.

TRNGs are mainly used for cryptography, because they are too slow for simulation purposes. Many true random numbers generators are hardware solutions that you plug to a computer. The usual method is to amplify noise generated by a resistoror a semi conductor diode and feeds this to a comparator or Schmitt trigger. Once you sample the output, you get a series of bits which can be used to generate random numbers.

True random numbers generators can be used for research, modeling, encryption, lottery prediction and parapsychological testing, among many other users.

So, as wee have disscussed both RNG and PRNG, the most obvious advantage of using PRNG over RNG is that

PRNGs have the appearance of randomness but they exhibit a specific repeatable pattern due to which it is easy for the encryptor to understand the pattern whereas it is equally difficult for the attacker to know the exacct pattern.

Other applications where PRNGs and RNGs can be used are as follows,

1. Simulation : When a computer is being used to simulate natural phenomena, random numbers are required to make things realistic. Simulation covers many fields, from the study of nuclear physics(where particles are subjected to random collisions) to operations research (where people come into, say, a railway station at random intervals).

2. Sampling : It is often impractical to examine all possible cases, but a random sample will provide an insight into what constitutes \"typical behaviour\".

3. Numerical Analysis: ingenious tecchniques for solving complicated numerical problems have been deviced using random numbers.

4. Computer Programming : Random values makes a good source of data for testing the effectiveness of computer algorithm.