PassGAN: A Deep Learning Approach for Password Guessing

Applied Cryptography and Network Security: 17th International Conference, ACNS 2019, Bogota, Colombia, June 5–7, 2019, Proceedings(2019)

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摘要
State-of-the-art password guessing tools, such as HashCat and John the Ripper, enable users to check billions of passwords per second against password hashes. In addition to performing straightforward dictionary attacks, these tools can expand password dictionaries using password generation rules, such as concatenation of words (e.g., “password123456”) and leet speak (e.g., “password” becomes “p4s5w0rd”). Although these rules work well in practice, creating and expanding them to model further passwords is a labor-intensive task that requires specialized expertise.
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关键词
Passwords,Privacy,Generative Adversarial Networks (GAN),Deep learning
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