頻域混音系統的自動化解密研究

Abstract

Extensive eavesdropping on phone extensions necessitates the development ofan end-to-end secure communication. Most commercial speech security equipmentsapply the analog scrambling technique, particularly the frequency-domain scramblerwhich derives its cryptanalytic strength from random permutation of speech spectrum.Since in most systems the security resides in the permutation (the key), it is worthdiscussing the processing of deducing correct key from insufficiently scrambled speech. A brute force attack requires an exhaustive search over the entire discretekeyspace and is obviously impractical. To overcome this problem, we propose an automated cryptanalysis approach in which the key search is realized in the maximum likelihood estimation process. For greater efficiency, this task can be formulated as one of the perfect matching problems that leads to search for the permutation associated the minimum cost. In the proposed system, we use the genetic algorithm to find the global optimal solution. As compared with Baum's iterative maximization algorithm, the genetic-based search is shown to yield better performance by taking into account the doubly stochastic constraint of the underlying keyspace.