Lecture_5

Random Numbers
Use of Random Numbers
Key distribution and authentication schemes
Generation of session keys or keys for RSA
Generation of bit stream for stream ciphers
Randomness
Uniform distribution: frequency of occurrence of 1’s and 0’s approximately equal
Independence: no sub-sequence can be inferred from others
Unpredictability
Hard to predict next value in sequence
True Random Number Generator
Non-deterministic source, physical environment
Detect ionizing radiation events, leaky capacitors, thermal noise from resistors or audio inputs
Mouse/keyboard activity, I/O operations, interrupts
Inconvenient, small number of values
Pseudo Random Number Generator
Deterministic algorithms to calculate numbers in “relatively random” sequence
Seed is algorithm input
Produces continuous stream of random bits
Pseudo Random Function
Same as PRNG but produces string of bits of some
Hard to determine pseudo-random stream if don’t know seed (but know algorithm)
Randomness
- Test for uniformity, scalability, consistency
- Examples: Frequency, runs, compressability
Unpredictability
- Forward and backward unpredictability
Seed must be secure
- Use TRNG to generate seed