(Q40537921)

English

Fast, Lean, and Accurate: Modeling Password Guessability Using Neural Networks

scientific article published on 2016

In more languages

edit

Statements

instance of

scholarly article

0 references

title

Fast, Lean, and Accurate: Modeling Password Guessability Using Neural Networks (English)

0 references

main subject

password strength

0 references

recurrent neural network

0 references

0 references

7

Lorrie Faith Cranor

0 references

author name string

William Melicher

series ordinal

1

0 references

Blase Ur

series ordinal

2

0 references

Sean M. Segreti

series ordinal

3

0 references

Saranga Komanduri

series ordinal

4

0 references

Lujo Bauer

series ordinal

5

0 references

Nicolas Christin

series ordinal

6

0 references

language of work or name

English

0 references

publication date

2016

0 references

source code repository URL

https://github.com/cupslab/neural_network_cracking

version control system

Git

web interface software

GitHub

0 references

full work available at URL

https://www.usenix.org/system/files/conference/usenixsecurity16/sec16_paper_melicher.pdf

0 references

published in

Proceedings of the 25th USENIX Security Symposium

0 references

page(s)

175-191

0 references

uses

Hashcat

1 reference

quotation

We compute guess numbers using the popular cracking tools Hashcat (English)

John the Ripper

1 reference

quotation

We compute guess numbers using the popular cracking tools Hashcat and John the Ripper (JtR). (English)

0 references

0 references

0 references

0 references

describes a project that uses

artificial neural network

1 reference

based on heuristic

inferred from title

(Q40537921)

Fast, Lean, and Accurate: Modeling Password Guessability Using Neural Networks

Statements

Sitelinks

Wikipedia(0 entries)

Wikibooks(0 entries)

Wikinews(0 entries)

Wikiquote(0 entries)

Wikisource(0 entries)

Wikiversity(0 entries)

Wikivoyage(0 entries)

Wiktionary(0 entries)

Multilingual sites(0 entries)