分割,重组和征服:语法模式-重组算法应用于密码猜测过程

Iwen Coisel, Ignacio Sanchez, Javier Galbally
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引用次数: 1

摘要

本文提出了一种基于识别、提取和重组人工选择密码中有意义的语法模式的新型密码猜测方法。该方法利用用户选择的密码中存在的这些模式,从而有效地减少了密码猜测过程中需要探索的搜索空间。密码猜测方案遵循两阶段策略。在第一步,一种基于机器学习原理的新算法,从密码数据集中识别和提取有语法意义的模式。然后,在第二阶段,这些先前分割的密码部分被重新组合,以生成新的统计相关的候选密码,这些候选密码用于盲评估集。实验结果表明,该方法对复杂密码具有较强的鲁棒性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Divide, recombine and conquer: Syntactic patterns-reassembly algorithm applied to password guessing process
This work proposes a novel password guessing approach based on the identification, extraction and recombination of meaningful syntactic patterns present in human-chosen passwords. The proposed method exploits the existence of these patterns across user-selected passwords in order to effectively reduce the search space to be explored during the password guessing process. The password guessing scheme follows a two stage strategy. In the first step, a novel algorithm based on machine learning principles, identifies and extracts the syntactic meaningful patterns from a dataset of passwords. Then, in a second stage, these parts-of-passwords previously segmented are recombined in order to generate new statistically relevant password candidates that are used against a blind evaluation set. The experimental results show that this novel approach is able to guess complex passwords usually robust to traditional password guessing techniques.
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