An evolutionary computation attack on one-round TEA

AbstractIn this work, one-round Tiny Encryption Algorithm (TEA) is attacked with an Evolutionary Computation method inspired by a combination of Genetic Algorithm (GA) and Harmony Search (HS). The system presented evaluates and evolves a population of candidate keys and compares paintext-ciphertext pairs of the known key against said population. We verify that randomly generated keys are the hardest to derive. Keys composed of words containing all on-bits are more difficult to break than keys composed of words containing all off-bits. Keys which have repeated words are easiest to derive. Finally, the present EC strategy is capable of deriving degenerate keys; this is most evident when keys are front loaded so that the first byte of each word has the highest density of on-bits

Cryptanalysis of RSA: Integer Prime Factorization Using Genetic Algorithms

In recent years, researchers have been exploring alternative methods to solving Integer Prime Factorization, the decomposition of an integer into its prime factors. This has direct application to cryptanalysis of RSA, as one means of breaking such a cryptosystem requires factorization of a large number that is the product of two prime numbers. This paper applies three different genetic algorithms to solve this issue, utilizing mathematical knowledge concerning distribution of primes to improve the algorithms. The best of the three genetic algorithms has a chromosome that represents m in the equation prime = 6 m ± 1, and is able to factor a number of up to 22 decimal digits. This is a significantly larger number than the largest factored by comparable methods in earlier work. This leads to the conclusion that approaches such as genetic algorithms are a promising avenue of research into the problem of integer factorization