[go: up one dir, main page]
More Web Proxy on the site http://driver.im/ skip to main content
10.1145/3424978.3425021acmotherconferencesArticle/Chapter ViewAbstractPublication PagescsaeConference Proceedingsconference-collections
research-article

Trie Tree Probabilistic Password Cracking Method Based on FPGA

Published: 20 October 2020 Publication History

Abstract

Password recovery technology is an important means of Internet electronic evidence. For the low hit rate and slow generation of password cracking, a trie tree probabilistic password cracking method based on FPGA is proposed. Firstly, through the leaked password set, we analyze the user password structure and study the correlation information between characters. Then using the trie tree time-space tradeoff structure features to build password trie tree, which can improve the cracking hit rate. Secondly, the high-speed trie tree password generation algorithm is designed and implemented on FPGA, which speeds up the password generation. Finally, heterogeneous systems are built with CPU and FPGA to achieve a complete application of this method, and some highperformance password recovery algorithms are attacked. The experimental results and analysis show that the password generation speed of this method is about 13 times higher than that of CPU. Compared with the JtR and PCFG attacks, the recovery efficiency and hit rate are improved, and this method has better practical value.

References

[1]
He D, Zhou B, Yang X, Chan S, et al. (2020). Group Password Strength Meter Based on Attention Mechanism. IEEE Network, 1--7.
[2]
He Y, Alem E E and Wang W (2020). Hybritus: a password strength checker by ensemble learning from the query feedbacks of websites. Frontiers of Computer Science in China, 14(3), 1--14.
[3]
Ophoff J and Dietz F (2019). Using Gamification to Improve Information Security Behavior: A Password Strength Experiment. IFIP Advances in Information and Communication Technology, 157--169.
[4]
Wang D, He D, Cheng H, et al. (2016). fuzzyPSM: A New Password Strength Meter Using Fuzzy Probabilistic Context-Free Grammars. 46th Annual IEEE/IFIP International Conference on Dependable Systems and Networks, 595--606.
[5]
Shay R, Komanduri S, Durity A L, et al. (2016). Designing Password Policies for Strength and Usability. ACM Transactions on Information and System Security, 18(4), 1--34.
[6]
Wheeler D L (2016). zxcvbn: Low-Budget Password Strength Estimation. USENIX Security Symposium, 157--173.
[7]
Xu L, Ge C, Qiu W, et al. (2017). Password Guessing Based on LSTM Recurrent Neural Networks. IEEE Computational Science and Engineering, 785--788.
[8]
Liu Y, Xia Z, Yi P, et al. (2018). GENPass: A General Deep Learning Model for Password Guessing with PCFG Rules and Adversarial Generation. International Conference on Communications, 1--6.
[9]
Deng G, Yu X, Guo H, et al. (2019). Efficient Password Guessing Based on a Password Segmentation Approach. IEEE Global Communications Conference, 1--6.
[10]
Shen J, Yuen T T, Choo K R, et al. (2019). AMOGAP: Defending Against Manin-the-Middle and Offline Guessing Attacks on Passwords. Australasian Conference on Information Security and Privacy, 514--532.
[11]
Hitaj B, Gasti P, Ateniese G, et al. (2017). PassGAN: A Deep Learning Approach for Password Guessing. Applied Cryptography and Network Security, 217--237.
[12]
Fang Y, Liu K, Fan J, et al. (2019). Password Guessing Based on Semantic Analysis and Neural Networks. Trusted Computing and Information Security, 84--98.
[13]
Wang D, Zhang Z, Wang P, Yan J and Huang X (2016). Targeted Online Password Guessing: An Underestimated Threat. Computer and Communications Security, 1242--1254.
[14]
Haoliang S and Dawei W (2019). Multi-step Trie Tree Packet Classification Method supporting Wildcards. IEEE 3rd Advanced Information Management, Communicates, Electronic and Automation Control Conference, 31--35.
[15]
Khern-Am-Nuai W, Hashim M J, Pinsonneault A, et al. (2017). Enhancing Operational Security by Redesigning Password Strength Meters: Evidence from Randomized Experiments. Proceedings of the 50th Hawaii International Conference on System Sciences, 587--596.
[16]
Wang D, Cheng H, Wang P, et al. (2017). Zipfs law in passwords. IEEE Transactions on Information Forensics and Security, 12(11), 2776--2791.
[17]
Wang P, Wang D and Xinyi H (2016). Advances in password security. Journal of Computer Research and Development, 53(10), 2173--2188.

Information & Contributors

Information

Published In

cover image ACM Other conferences
CSAE '20: Proceedings of the 4th International Conference on Computer Science and Application Engineering
October 2020
1038 pages
ISBN:9781450377720
DOI:10.1145/3424978
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

Publisher

Association for Computing Machinery

New York, NY, United States

Publication History

Published: 20 October 2020

Permissions

Request permissions for this article.

Check for updates

Author Tags

  1. FPGA
  2. Password recovery
  3. Password structure
  4. Regular expression
  5. Trie tree

Qualifiers

  • Research-article
  • Research
  • Refereed limited

Conference

CSAE 2020

Acceptance Rates

CSAE '20 Paper Acceptance Rate 179 of 387 submissions, 46%;
Overall Acceptance Rate 368 of 770 submissions, 48%

Contributors

Other Metrics

Bibliometrics & Citations

Bibliometrics

Article Metrics

  • 0
    Total Citations
  • 95
    Total Downloads
  • Downloads (Last 12 months)8
  • Downloads (Last 6 weeks)1
Reflects downloads up to 16 Dec 2024

Other Metrics

Citations

View Options

Login options

View options

PDF

View or Download as a PDF file.

PDF

eReader

View online with eReader.

eReader

Media

Figures

Other

Tables

Share

Share

Share this Publication link

Share on social media