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A password strength evaluation algorithm based on sensitive personal information

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

11 Scopus citations

Abstract

Many Internet service providers are still using traditional password strength evaluation methods, resulting in user passwords being vulnerable to social engineering attacks. We believe that the password strength evaluation method based on sensitive personal information has great research value for improving the security of password authentication system. In this paper, we use the structure segmentation algorithm and the bidirectional matching algorithm to investigate how users' personal information is used in passwords. Then, we present a sensitivity personal information coverage evaluation function that represents the correlation between users' password and their personal information. Finally, a password strength evaluation method based on sensitive personal information is proposed. This method is composed of three stages: preprocessing stage, prediction dictionary generation stage and password strength evaluation stage.

Original languageEnglish
Title of host publicationProceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
EditorsGuojun Wang, Ryan Ko, Md Zakirul Alam Bhuiyan, Yi Pan
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1542-1545
Number of pages4
ISBN (Electronic)9781665403924
DOIs
StatePublished - Dec 2020
Externally publishedYes
Event19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020 - Guangzhou, China
Duration: 29 Dec 20201 Jan 2021

Publication series

NameProceedings - 2020 IEEE 19th International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020

Conference

Conference19th IEEE International Conference on Trust, Security and Privacy in Computing and Communications, TrustCom 2020
Country/TerritoryChina
CityGuangzhou
Period29/12/201/01/21

Keywords

  • Data mining
  • Information security
  • Password authentication
  • Password strength evaluation method

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