Technical Writing: Introduction (revised)

Thursday, November 23, 2006

Introduction (revised)

Note from Jati

Pseudo Random Number Generator

Chaos theory has been established since 1970s by many different research areas, such as physics, mathematics, biology and chemistry, etc. [ give an example here] The most well-known characteristics of chaos is pseudo-randomness generated by deterministic equations. Randomness is a very useful resource, and nowhere more than in cryptographic applications. Randomness is essential for secret keys, and inadequate source of randomness can compromise the strongest cryptographic protocol. [example of the application] However, the reality is that procedures for obtaining random bits (called pseudo-random generators) are often not designed as well as they could have been. This is unfortunate since a security flaw in this procedure translates into a security flaw in the whole system. Also, if this procedure does not have a rigorous security proof then there is no hope for such a proof for the whole system.

[A very good introduction; you have to give example of the use in real life]

Random numbers are heavily used in cryptography. Session keys, initialization vectors (IV), unique parameters in digital signature operations, are assumed to be random by cryptographer. What random means here is the numbers generated by system are hard to be predicted by an attacker. [example of the application] Unfortunately, in practice, it is very difficult to get pure random numbers. Many cryptographic applications don't have a reliable source of real random bits. So, a cryptographic mechanism called a Pseudo-Random Number Generator (PRNG) is used to generate these numbers. The numbers are said to be Pseudo-Random because they are produced by some mathematical formulas and so periodically repeat themselves. A well-defined Pseudo-Random Number Generator - used for cryptography application - is called Cryptographically Secure Pseudo-Random Number Generator. It should statistically has good characteristic and endure all serious attacks. [example of the application]

Things that will be explained in this paper :

• Requirement for PRNG

• Implementation of Old PRNG Algorithm

• Implementation of Modern PRNG Algorithm

• Cryptanalytic Attacks on Real-World PRNG

Author:

13504060 dani

13504080 stevens jethefer

General note;

You need to give examples for the explanation so that the reader get clearer picture.

Chaos theory has been established since 1970s by many different research areas, such as physics, mathematics, biology and chemistry, etc. The most well-known characteristics of chaos is pseudo-randomness generated by deterministic equations. Randomness is a very useful resource, and nowhere more than in cryptographic applications. Randomness is essential for secret keys, and inadequate source of randomness can compromise the strongest cryptographic protocol. However, the reality is that procedures for obtaining random bits (called pseudo-random generators) are often not designed as well as they could have been. This is unfortunate since a security flaw in this procedure translates into a security flaw in the whole system. Also, if this procedure does not have a rigorous security proof then there is no hope for such a proof for the whole system.

Random numbers are heavily used in cryptography. Session keys, initialization vectors (IV), unique parameters in digital signature operations, are assumed to be random by cryptographer. What random means here is the numbers generated by system are hard to be predicted by an attacker. Unfortunately, in practice, it is very difficult to get pure random numbers. Many cryptographic applications don't have a reliable source of real random bits. So, a cryptographic mechanism called a Pseudo-Random Number Generator (PRNG) is used to generate these numbers. The numbers are said to be Pseudo-Random because they are produced by some mathematical formulas and so periodically repeat themselves. A well-defined Pseudo-Random Number Generator - used for cryptography application - is called Cryptographically Secure Pseudo-Random Number Generator. It should statistically has good characteristic and endure all serious attacks.