Corpus ID: 63933670

An Investigation of Machine Learning for Password Evaluation

@inproceedings{Todd2016AnIO,
  title={An Investigation of Machine Learning for Password Evaluation},
  author={M Todd},
  year={2016}
}
  • M. Todd
  • Published 2016
  • Computer Science
Introducing a Machine Learning Password Metric Based on EFKM Clustering Algorithm
TLDR
A password strength metric using Enhanced Fuzzy K-Means clustering algorithm (EFKM) is introduced, able to recognize all the passwords from the OWASP as weak passwords only and regarding the leaked passwords, the metric recognizes almost the entire set of weak passwords. Expand
Nuevo modelo probabilístico en autenticación gráfica
La autenticacion es esencial en la seguridad de los modernos servicios digitales de procesamiento de informacion. Las contrasenas alfanumericas son las mas empleadas, pero poseen debilidades que lasExpand

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Among the longer policies, new evidence for a security/usability tradeoff is discovered, with none being strictly better than another on both dimensions, however, several policies are both more usable and more secure that the traditional policy the authors tested. Expand
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It is found that participants create far fewer weak passwords using the Telepathword-based policies than policies based only on character composition, and participants using Telepathwords were also more likely to report that the password feedback was helpful. Expand
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It was found that meters with a variety of visual appearances led users to create longer passwords, however, significant increases in resistance to a password-cracking algorithm were only achieved using meters that scored passwords stringently. Expand
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This paper attempts to determine the effectiveness of using entropy, as defined in NIST SP800-63, as a measurement of the security provided by various password creation policies, by modeling the success rate of current password cracking techniques against real user passwords. Expand
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TLDR
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zxcvbn: Low-Budget Password Strength Estimation
  • Dan Wheeler
  • Computer Science
  • USENIX Security Symposium
  • 2016
For over 30 years, password requirements and feedback have largely remained a product of LUDS: counts of lowerand uppercase letters, digits and symbols. LUDS remains ubiquitous despite being aExpand
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