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Title: GitHub - RUB-SysSec/NEMO: Modeling Password Guessability Using Markov Models · GitHub

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Description: Modeling Password Guessability Using Markov Models - RUB-SysSec/NEMO

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READMEhttps://github.com/RUB-SysSec/NEMO
https://github.com/RUB-SysSec/NEMO#nemo-modeling-password-guessability-using-markov-models
https://github.com/RUB-SysSec/NEMO#tldr
https://github.com/RUB-SysSec/NEMO#warning
PyPyhttps://pypy.org/download.html
https://github.com/RUB-SysSec/NEMO#about-nemo
OMENhttps://github.com/RUB-SysSec/OMEN
herehttps://www.mobsec.ruhr-uni-bochum.de/forschung/veroeffentlichungen/omen/
herehttps://www.mobsec.ruhr-uni-bochum.de/media/mobsec/arbeiten/2014/12/12/2013-ma-angelstorf-omen.pdf
Matthew Weirhttps://dblp.uni-trier.de/pers/hd/w/Weir:Matt
@lakiwhttps://twitter.com/lakiw
herehttps://github.com/lakiw/py_omen
https://github.com/RUB-SysSec/NEMO#difference-to-omen
more accurate strength estimateshttps://www.mobsec.ruhr-uni-bochum.de/forschung/veroeffentlichungen/accuracy-password-strength-meters/
https://github.com/RUB-SysSec/NEMO#overview-markov-model-based-password-guessing
Arvind Narayananhttps://dblp.uni-trier.de/pers/hd/n/Narayanan:Arvind
Vitaly Shmatikovhttps://dblp.uni-trier.de/pers/hd/s/Shmatikov:Vitaly
Fast Dictionary Attacks on Passwords Using Time-Space Tradeoffhttps://www.cs.cornell.edu/~shmat/shmat_ccs05pwd.pdf
John the Ripperhttps://www.openwall.com/john/
herehttps://github.com/magnumripper/JohnTheRipper/blob/bleeding-jumbo/doc/MARKOV
herehttps://openwall.info/wiki/john/markov
herehttps://github.com/RUB-SysSec/Password-Guessing-Framework/blob/master/src/scripts/JTR_MARKOV.sh
Simon Marechalhttps://dblp.uni-trier.de/pers/hd/m/Marechal:Simon
@bartavellehttps://twitter.com/bartavelle
Advances in Password Crackinghttps://link.springer.com/article/10.1007/s11416-007-0064-y
Dell’Amico et al.https://dblp.uni-trier.de/pers/hd/d/Dell=Amico:Matteo
Measuring Password Strength: An Empirial Analysishttps://arxiv.org/pdf/0907.3402.pdf
Castelluccia et al.https://dblp.uni-trier.de/pers/hd/c/Castelluccia:Claude
Dürmuth et al.https://dblp.uni-trier.de/pers/hd/d/D=uuml=rmuth:Markus
Adaptive Password-Strength Meters from Markov Modelshttps://www.ei.ruhr-uni-bochum.de/media/ei/veroeffentlichungen/2016/01/15/2012-ndss-pwd-strength.pdf
OMEN: Faster Password Guessing Using an Ordered Markov Enumeratorhttps://hal.archives-ouvertes.fr/hal-01112124/document
When Privacy Meets Security: Leveraging Personal Information for Password Crackinghttps://arxiv.org/pdf/1304.6584.pdf
Ma et al.https://dblp.uni-trier.de/pers/hd/m/Ma:Jerry
A Study of Probabilistic Password Modelshttps://www.ieee-security.org/TC/SP2014/papers/AStudyofProbabilisticPasswordModels.pdf
Matteo Dell’Amicohttps://dblp.uni-trier.de/pers/hd/d/Dell=Amico:Matteo
Maurizio Filipponehttps://dblp.uni-trier.de/pers/hd/f/Filippone:Maurizio
Monte Carlo Strength Evaluation: Fast and Reliable Password Checkinghttp://www.eurecom.fr/~filippon/Publications/ccs15.pdf
backoffhttps://github.com/matteodellamico/montecarlopwd
Ur et al.https://dblp.uni-trier.de/pers/hd/u/Ur:Blase
Measuring Real-World Accuracies and Biases in Modeling Password Guessabilityhttps://www.blaseur.com/papers/sec15-guessability.pdf
Password Guessability Service (PGS)https://pgs.ece.cmu.edu/
Melicher et al.https://dblp.uni-trier.de/pers/hd/m/Melicher:William
Fast, Lean, and Accurate: Modeling Password Guessability Using Neural Networkshttps://www.usenix.org/conference/usenixsecurity16/technical-sessions/presentation/melicher
model can be found on GitHubhttps://github.com/cupslab/neural_network_cracking/blob/master/markov_model.py
https://github.com/RUB-SysSec/NEMO#publications
Reasoning Analytically About Password-Cracking Softwarehttps://www.mobsec.ruhr-uni-bochum.de/forschung/veroeffentlichungen/reasoning-analytically-about-password-cracking/
On the Accuracy of Password Strength Metershttps://www.mobsec.ruhr-uni-bochum.de/forschung/veroeffentlichungen/accuracy-password-strength-meters/
On the Security of Cracking-Resistant Password Vaultshttps://www.mobsec.ruhr-uni-bochum.de/forschung/veroeffentlichungen/cracking-resistant-password-vaults/
Emojihttps://www.mobsec.ruhr-uni-bochum.de/forschung/veroeffentlichungen/quantifying-security-emoji-based-authentication/
Android unlock patternshttps://www.mobsec.ruhr-uni-bochum.de/forschung/veroeffentlichungen/accuracy-android-pattern-strength-meters/
https://github.com/RUB-SysSec/NEMO#design-decisions
https://github.com/RUB-SysSec/NEMO#how-big-are-they
https://github.com/RUB-SysSec/NEMO#some-details-for-the-ones-interested
backoffhttps://github.com/matteodellamico/montecarlopwd
https://github.com/RUB-SysSec/NEMO#development
dictionaries are always orderedhttps://mail.python.org/pipermail/python-dev/2017-December/151283.html
https://github.com/RUB-SysSec/NEMO#performance-testing
PyPyhttps://pypy.org/download.html
https://github.com/RUB-SysSec/NEMO#getting-started
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https://github.com/RUB-SysSec/NEMO#training
https://github.com/RUB-SysSec/NEMO#training-requirements
https://github.com/RUB-SysSec/NEMO#how-to-train-the-model
MessagePackhttps://github.com/vsergeev/u-msgpack-python
https://github.com/RUB-SysSec/NEMO#strength-estimation
https://github.com/RUB-SysSec/NEMO#faq
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https://github.com/RUB-SysSec/NEMO#contact
websitehttps://www.mobsec.rub.de
Twitterhttps://twitter.com/hgi_bochum
International Conference on Passwords (PASSWORDS)https://passwordscon.org
markov https://github.com/topics/markov
password https://github.com/topics/password
strength https://github.com/topics/strength
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