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Conference Papers Year : 2012

Adaptive Password-Strength Meters from Markov Models

Abstract

Measuring the strength of passwords is crucial to ensure the security of password-based authentication. However, current methods to measure password strength have limited accuracy, first, because they use rules that are too simple to capture the complexity of passwords, and second, because password frequencies widely differ from one application to another. In this paper, we present the concept of adaptive password strength meters that estimate password strength using Markov-models. We propose a secure implementation that greatly improves on the accuracy of current techniques.
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Dates and versions

hal-00747824 , version 1 (02-11-2012)

Identifiers

  • HAL Id : hal-00747824 , version 1

Cite

Claude Castelluccia, Durmuth Markus, Daniele Perito. Adaptive Password-Strength Meters from Markov Models. NDSS 2012 - 19th Annual Network & Distributed System Security Symposium, ISOC, Feb 2012, San Diego, United States. ⟨hal-00747824⟩

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