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DPPG: A Dynamic Password Policy Generation System
- Source :
- IEEE Transactions on Information Forensics and Security. 13:545-558
- Publication Year :
- 2018
- Publisher :
- Institute of Electrical and Electronics Engineers (IEEE), 2018.
-
Abstract
- To keep password users from creating simple and common passwords, major websites and applications provide a password-strength measure, namely a password checker. While critical requirements for a password checker to be stringent have prevailed in the study of password security, we show that regardless of the stringency, such static checkers can leak information and actually help the adversary enhance the performance of their attacks. To address this weakness, we propose and devise the Dynamic Password Policy Generator , namely DPPG , to be an effective and usable alternative to the existing password strength checker. DPPG aims to enforce an evenly-distributed password space and generate dynamic policies for users to create passwords that are diverse and that contribute to the overall security of the password database. Since DPPG is modular and can function with different underlying metrics for policy generation, we further introduce a diversity-based password security metric that evaluates the security of a password database in terms of password space and distribution. The metric is useful as a countermeasure to well-crafted offline cracking algorithms and theoretically illustrates why DPPG works well.
- Subjects :
- Password
021110 strategic, defence & security studies
Password policy
Zero-knowledge password proof
Software_OPERATINGSYSTEMS
Cognitive password
Computer Networks and Communications
Salt (cryptography)
Computer science
0211 other engineering and technologies
Password cracking
Passphrase
02 engineering and technology
Adversary
Computer security
computer.software_genre
One-time password
S/KEY
Password strength
ComputingMilieux_MANAGEMENTOFCOMPUTINGANDINFORMATIONSYSTEMS
0202 electrical engineering, electronic engineering, information engineering
Key stretching
020201 artificial intelligence & image processing
Safety, Risk, Reliability and Quality
computer
Subjects
Details
- ISSN :
- 15566021 and 15566013
- Volume :
- 13
- Database :
- OpenAIRE
- Journal :
- IEEE Transactions on Information Forensics and Security
- Accession number :
- edsair.doi...........0b75c19f5ca953203db05457d15ba087
- Full Text :
- https://doi.org/10.1109/tifs.2017.2737971