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The security of modern password expiration: an algorithmic framework and empirical analysis
Abstract
This paper presents the first large-scale study of the success of password expiration in meeting its intended purpose, namely revoking access to an account by an attacker who has captured the account's password. Using a dataset of over 7700 accounts, we assess the extent to which passwords that users choose to replace expired ones pose an obstacle to the attacker's continued access. We develop a framework by which an attacker can search for a user's new password from an old one, and design an efficient algorithm to build an approximately optimal search strategy. We then use this strategy to measure the difficulty of breaking newly chosen passwords from old ones. We believe our study calls into question the merit of continuing the practice of password expiration.
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Citations
Cited by
The Science of Guessing: Analyzing an Anonymized Corpus of 70 Million Passwords
Bonneau, J. (2012) · 2012 IEEE Symposium on Security and Privacy · doi:10.1109/sp.2012.49 · Cited by 687
FIDO Gets Verified: A Formal Analysis of the Universal Authentication Framework Protocol
Feng, H., Guan, J., Li, H., Pan, X., & Zhao, Z. (2023) · IEEE Transactions on Dependable and Secure Computing · doi:10.1109/tdsc.2022.3217259 · Cited by 13
Metadata
- Authors
- Zhang, Y., Monrose, F., & Reiter, M. K.
- Venue
- Proceedings of the 17th ACM conference on Computer and communications security
- Publisher
- ACM
- Published
- 2010-10-04
- Pages
- 176-186
- ISSN
- 1543-7221 (ISSN-L)
- OpenAlex
- W2091833612
- Cited by
- 169
- References
- 0
- FWCI
- 5.17
- Type
- conference paper
- Language
- en
- Open access
- closed
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- CoChat. (2026). Citation check: The security of modern password expiration: an algorithmic framework and empirical analysis. https://app.cochat.ai/papers/10.1145/1866307.1866328
- The paper
- Zhang, Y., Monrose, F., & Reiter, M. K. (2010). The security of modern password expiration: an algorithmic framework and empirical analysis. Proceedings of the 17th ACM conference on Computer and communications security. https://doi.org/10.1145/1866307.1866328
Data sources
Bibliographic data: Semantic Scholar, OpenAlex, Crossref.
Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
Semantic Scholar’s data is described in: Kinney, R., et al. (2023). The Semantic Scholar Open Data Platform. arXiv:2301.10140.