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Measuring Real-World Accuracies and Biases in Modeling Password Guessability., , , , , , , , , and . USENIX Security Symposium, page 463-481. USENIX Association, (2015)Designing Password Policies for Strength and Usability., , , , , , , , , and . ACM Trans. Inf. Syst. Secur., 18 (4): 13:1-13:34 (2016)Comprehension from Chaos: What Users Understand and Expect from Private Computation., , , , and . CoRR, (2022)Supporting Password-Security Decisions with Data.. Carnegie Mellon University, USA, (2016)Analysis of Google Ads Settings Over Time: Updated, Individualized, Accurate, and Filtered., , , and . WPES@CCS, page 167-172. ACM, (2023)"It's Stored, Hopefully, on an Encrypted Server": Mitigating Users' Misconceptions About FIDO2 Biometric WebAuthn., , , and . USENIX Security Symposium, page 91-108. USENIX Association, (2021)AutoTap: synthesizing and repairing trigger-action programs using LTL properties., , , , , and . ICSE, page 281-291. IEEE / ACM, (2019)A Spoonful of Sugar?: The Impact of Guidance and Feedback on Password-Creation Behavior., , , , , , , , , and . CHI, page 2903-2912. ACM, (2015)Taking Data Out of Context to Hyper-Personalize Ads: Crowdworkers' Privacy Perceptions and Decisions to Disclose Private Information., , , , , and . CHI, page 1-13. ACM, (2020)User Perceptions of the Usability and Security of Smartphones as FIDO2 Roaming Authenticators., , , and . SOUPS @ USENIX Security Symposium, page 57-76. USENIX Association, (2021)