Conference paper

HRANICKÝ Radek, MATOUŠEK Petr, RYŠAVÝ Ondřej and VESELÝ Vladimír. Experimental Evaluation of Password Recovery in Encrypted Documents. In: Proceedings of ICISSP 2016. Roma: SciTePress - Science and Technology Publications, 2016, pp. 299-306. ISBN 978-989-758-167-0. Available from:
Publication language:english
Original title:Experimental Evaluation of Password Recovery in Encrypted Documents
Title (cs):Experimentální vyhodnocení nástrojů pro obnovu hesel u šifrovaných dokumentů
Proceedings:Proceedings of ICISSP 2016
Conference:2nd International Conference on Information Systems Security and Privacy
Place:Roma, IT
Publisher:SciTePress - Science and Technology Publications
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Password Recovery, Privacy, Digital Forensics, Encrypted Documents
Many document formats and archiving tools (PDF, DOC, ZIP) support encryption to protect privacy of the sensitive contents. The encryption is based on common cryptography algorithms as AES, SHA, RC4. For forensic purposes, investigators are often challenged to analyze these encrypted documents. The task of password recovery can be solved by exhaustive state space search using dictionaries or password generators augmented with heuristic rules to speed up the recovery. In our experimental study, we focus on the password recovery of popular document and archiving formats using parallel computation on common hardware with multicore CPUs or accelerated with GPU processors. We show how recovery time can be estimated based on alphabet, maximal password length and performance of given hardware. Our results are demonstrated on Wrathion, a tool developed by our research team.
   author = {Radek Hranick{\'{y}} and Petr Matou{\v{s}}ek and
	Ond{\v{r}}ej Ry{\v{s}}av{\'{y}} and Vladim{\'{i}}r
   title = {Experimental Evaluation of Password Recovery in
	Encrypted Documents},
   pages = {299--306},
   booktitle = {Proceedings of ICISSP 2016},
   year = {2016},
   location = {Roma, IT},
   publisher = {SciTePress - Science and Technology Publications},
   ISBN = {978-989-758-167-0},
   doi = {10.5220/0005685802990306},
   language = {english},
   url = {}

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