The automated cryptanalysis of DFT-based speech scramblers

Abstract

An automated method For cryptanalysis of DFT-based analog speech scramblers is presented through statistical estimation treatments. In the proposed system, the cipher-text only attack is formulated as a combinatorial optimization problem leading to a search for the most likely key estimate. For greater efficiency, we also explore the benefits of genetic algorithm to develop an estimation method which takes into account the doubly stochastic characteristics of the underlying keyspace. Simulation results: indicate that the global explorative properties of genetic algorithms make them very effective at estimating the most likely permutation and by using this estimate significant amount of the intelligibility can be recovered from the ciphertext following the attack on DFT-based speech scramblers.