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Statistics on Password Re-use and Adaptive Strength for Financial Accounts

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Security and Cryptography for Networks (SCN 2014)

Part of the book series: Lecture Notes in Computer Science ((LNSC,volume 8642))

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Abstract

Multiple studies have demonstrated that users select weak passwords. However, the vast majority of studies on password security uses password lists that only have passwords for one site, which means that several important questions cannot be studied. For example, how much stronger are password choices for different categories of sites? We use a dataset which we extracted from a large dump of malware records. It contains multiple accounts (and passwords) per user and thus allows us to study both password re-use and the correlation between the value of an account and the strength of the passwords for those accounts.

The first contribution of our study shows that users in our sample choose (substantially) stronger passwords for financial accounts than for low-value accounts, based on the extracted passwords as well as publicly available lists. This contribution has implications for password research, as some widely-used lists contain passwords much weaker than those used in the real world (for accounts of more than low value). In our second contribution, we measure password re-use taking account values into account. We see that although high-value passwords are stronger, they are re-used more frequently than low-value passwords – valuable passwords are identical to 21% of the remaining passwords of a user. Before our study, little was known about password re-use for different account values.

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Bailey, D.V., Dürmuth, M., Paar, C. (2014). Statistics on Password Re-use and Adaptive Strength for Financial Accounts. In: Abdalla, M., De Prisco, R. (eds) Security and Cryptography for Networks. SCN 2014. Lecture Notes in Computer Science, vol 8642. Springer, Cham. https://doi.org/10.1007/978-3-319-10879-7_13

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  • DOI: https://doi.org/10.1007/978-3-319-10879-7_13

  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-319-10878-0

  • Online ISBN: 978-3-319-10879-7

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