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DeepPhish: Understanding User Trust Towards Artificially Generated Profiles in Online Social Networks.

, , , , , and . USENIX Security Symposium, page 1669-1686. USENIX Association, (2022)

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On the Forensic Validity of Approximated Audit Logs., , , , , and . ACSAC, page 189-202. ACM, (2020)Users Can Deduce Sensitive Locations Protected by Privacy Zones on Fitness Tracking Apps., , , , and . CHI, page 448:1-448:21. ACM, (2022)SoK: History is a Vast Early Warning System: Auditing the Provenance of System Intrusions., , , , , , , , and . SP, page 2620-2638. IEEE, (2023)"Security is not my field, I'm a stats guy": A Qualitative Root Cause Analysis of Barriers to Adversarial Machine Learning Defenses in Industry., , , , and . USENIX Security Symposium, page 3763-3780. USENIX Association, (2023)Beyond Bot Detection: Combating Fraudulent Online Survey Takers✱., , , , , and . WWW, page 699-709. ACM, (2022)Everybody's Got ML, Tell Me What Else You Have: Practitioners' Perception of ML-Based Security Tools and Explanations., , , , , , and . SP, page 2068-2085. IEEE, (2023)SoK (or SoLK?): On the Quantitative Study of Sociodemographic Factors and Computer Security Behaviors., , , , , and . CoRR, (2024)It's Trying Too Hard To Look Real: Deepfake Moderation Mistakes and Identity-Based Bias., , , , , , and . CHI, page 778:1-778:20. ACM, (2024)DeepPhish: Understanding User Trust Towards Artificially Generated Profiles in Online Social Networks., , , , , and . USENIX Security Symposium, page 1669-1686. USENIX Association, (2022)FAuST: Striking a Bargain between Forensic Auditing's Security and Throughput., , , , , , , and . ACSAC, page 813-826. ACM, (2022)