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Cloak and Swagger: Understanding Data Sensitivity through the Lens of User Anonymity.

, , , and . IEEE Symposium on Security and Privacy, page 493-508. IEEE Computer Society, (2014)

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On the effectiveness of anonymizing networks for web search privacy., and . AsiaCCS, page 483-489. ACM, (2011)On the Privacy of Web Search Based on Query Obfuscation: A Case Study of TrackMeNot., and . Privacy Enhancing Technologies, volume 6205 of Lecture Notes in Computer Science, page 19-37. Springer, (2010)Reducing Permission Requests in Mobile Apps., , , , , , and . Internet Measurement Conference, page 259-266. ACM, (2019)User Anonymity on Twitter., , and . IEEE Secur. Priv., 15 (3): 84-87 (2017)Exploring decision making with Android's runtime permission dialogs using in-context surveys., , , and . SOUPS, page 195-210. USENIX Association, (2017)Evaluating Privacy Perceptions, Experience, and Behavior of Software Development Teams., , , and . SOUPS @ USENIX Security Symposium, page 101-120. USENIX Association, (2024)Cover locations: availing location-based services without revealing the location., , and . WPES, page 143-152. ACM, (2011)Privacy Risks of General-Purpose AI Systems: A Foundation for Investigating Practitioner Perspectives., , , , , and . CoRR, (2024)Towards Fine-Grained Localization of Privacy Behaviors., , , and . EuroS&P, page 258-277. IEEE, (2023)Hark: A Deep Learning System for Navigating Privacy Feedback at Scale., , , , and . SP, page 2469-2486. IEEE, (2022)