Besides, we propose to use benchmark passwords to show the relative strength of a password. Then, to balance efficiency and precision, we use Long Short-Term Memory to calculate the probabilities of alphanumeric strings.
TEAMSID WORST PASSWORDS 2016 PASSWORD
First, we classify password reuse behaviors into capitalization and those that use special characters for leet or separation, and calculate the corresponding probabilities. On the basis of fuzzyPSM, we propose a new PSM based on Reuse, Leet and Separation, namely RLS-PSM. FuzzyPSM considers password reuse, six major leet transformations and initial capitalization, and performs the best as evaluated by Golla and Dürmuth at ACM CCS’18. Except for fuzzyPSM, all PSMs assume passwords are newly constructed, which is not true in reality. Password strength meters (PSMs) are being widely used, but they often give conflicting, inaccurate and misleading feedback, which defeats their purpose. These results encourage the deployment of our proposed approach in comparison to traditional PIN and OTP systems where the attack would have 100% success rate under the same impostor scenario. 4.0% when the attacker knows the password. Finally, we discuss specific details for the deployment of our proposed approach on current PIN and OTP systems, achieving results with Equal Error Rates (EERs) ca.
This database is used in the experiments reported in this work and it is available together with benchmark results in GitHub. The new e-BioDigit database, which comprises on-line handwritten digits from 0 to 9, has been acquired using the finger as input on a mobile device.
A complete analysis of our proposed biometric system is carried out regarding the discriminative power of each handwritten digit and the robustness when increasing the length of the password and the number of enrolment samples. In our proposed approach, users draw each digit of the password on the touchscreen of the device instead of typing them as usual. This work enhances traditional authentication systems based on Personal Identification Numbers (PIN) and One-Time Passwords (OTP) through the incorporation of biometric information as a second level of user authentication.
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