Publication detail

Distributed PCFG Password Cracking

HRANICKÝ, R. ZOBAL, L. RYŠAVÝ, O. KOLÁŘ, D. MIKUŠ, D.

Original Title

Distributed PCFG Password Cracking

English Title

Distributed PCFG Password Cracking

Type

conference paper

Language

en

Original Abstract

In digital forensics, investigators frequently face cryptographic protection that prevents access to potentially significant evidence. Since users prefer passwords that are easy to remember, they often unwittingly follow a series of common password-creation patterns. A probabilistic context-free grammar is a mathematical model that can describe such patterns and provide a smart alternative for traditional brute-force and dictionary password guessing methods. Because more complex tasks require dividing the workload among multiple nodes, in the paper, we propose a technique for distributed cracking with probabilistic grammars.

English abstract

In digital forensics, investigators frequently face cryptographic protection that prevents access to potentially significant evidence. Since users prefer passwords that are easy to remember, they often unwittingly follow a series of common password-creation patterns. A probabilistic context-free grammar is a mathematical model that can describe such patterns and provide a smart alternative for traditional brute-force and dictionary password guessing methods. Because more complex tasks require dividing the workload among multiple nodes, in the paper, we propose a technique for distributed cracking with probabilistic grammars.

Keywords

distributed,password,cracking,forensics,grammar

Released

14.08.2020

Publisher

Springer Nature Switzerland AG

Location

Guildford

ISBN

978-3-030-58950-9

Book

Computer Security - ESORICS 2020

Edition

Lecture notes in Computer Science

Edition number

NEUVEDEN

Pages from

701

Pages to

719

Pages count

19

URL

Documents

BibTex


@inproceedings{BUT168120,
  author="Radek {Hranický} and Lukáš {Zobal} and Ondřej {Ryšavý} and Dušan {Kolář} and Dávid {Mikuš}",
  title="Distributed PCFG Password Cracking",
  annote="In digital forensics, investigators frequently face cryptographic protection that
prevents access to potentially significant evidence. Since users prefer passwords
that are easy to remember, they often unwittingly follow a series of common
password-creation patterns. A probabilistic context-free grammar is
a mathematical model that can describe such patterns and provide a smart
alternative for traditional brute-force and dictionary password guessing methods.
Because more complex tasks require dividing the workload among multiple nodes, in
the paper, we propose a technique for distributed cracking with probabilistic
grammars.",
  address="Springer Nature Switzerland AG",
  booktitle="Computer Security - ESORICS 2020",
  chapter="168120",
  doi="10.1007/978-3-030-58951-6_34",
  edition="Lecture notes in Computer Science",
  howpublished="print",
  institution="Springer Nature Switzerland AG",
  year="2020",
  month="august",
  pages="701--719",
  publisher="Springer Nature Switzerland AG",
  type="conference paper"
}