基于离散GANs的无监督密码破解
Unsupervised Cipher Cracking Using Discrete GANs
摘要：
这项工作详细介绍了CipherGAN，这是一种受CycleGAN启发的架构，用于推断给定未配对密文和明文库的底层密码映射。我们证明了CipherGAN能够使用移位和Vigenere密码以高度的保真度和比以前实现的大得多的词汇量来破解语言数据enciptering。我们介绍了如何CycleGAN可以兼容离散数据和训练在一个稳定的方式。然后，我们证明了CipherGAN中使用的技术避免了与应用于离散数据的GANs相关的无信息歧视的常见问题。
英文摘要：
This work details CipherGAN, an architecture inspired by CycleGAN used for inferring the underlying cipher mapping given banks of unpaired ciphertext and plaintext. We demonstrate that CipherGAN is capable of cracking language data enciphered using shift and Vigenere ciphers to a high degree of fidelity and for vocabularies much larger than previously achieved. We present how CycleGAN can be made compatible with discrete data and train in a stable way. We then prove that the technique used in CipherGAN avoids the common problem of uninformative discrimination associated with GANs applied to discrete data.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
