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 retrieve complex passwords usually robust to traditional password guessing techniques.

COISEL Iwen;  SANCHEZ MARTIN Jose Ignacio;  GALBALLY HERRERO Javier; 

2018-01-09

INSTITUTE OF ELECTRICAL AND ELECTRONICS ENGINEERS

JRC107390

2153-0742,   

http://ieeexplore.ieee.org/document/8167849/,    https://publications.jrc.ec.europa.eu/repository/handle/JRC107390,   

10.1109/CCST.2017.8167849,