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Personalised Privacy by Default Preferences - Experiment and Analysis.

, , , and . ICISSP, page 53-62. SciTePress, (2016)

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User Study of the Effectiveness of a Privacy Policy Summarization Tool., , , and . ICISSP (Revised Selected Papers), volume 1221 of Communications in Computer and Information Science, page 186-206. Springer, (2019)Default Privacy Setting Prediction by Grouping User's Attributes and Settings Preferences., , , and . DPM/CBT@ESORICS, volume 10436 of Lecture Notes in Computer Science, page 107-123. Springer, (2017)Explainable Machine Learning for Default Privacy Setting Prediction., , , and . IEEE Access, (2021)Challenges in Detecting Privacy Revealing Information in Unstructured Text., , and . PrivOn@ISWC, volume 1750 of CEUR Workshop Proceedings, CEUR-WS.org, (2016)Towards Exploring User Perception of a Privacy Sensitive Information Detection Tool., , and . ICISSP, page 628-634. SCITEPRESS, (2021)pQUANT: A User-Centered Privacy Risk Analysis Framework., , , and . CRiSIS, volume 12026 of Lecture Notes in Computer Science, page 3-16. Springer, (2019)Assessing Privacy Policies of Internet of Things Services., , , , and . SEC, volume 529 of IFIP Advances in Information and Communication Technology, page 156-169. Springer, (2018)Personalised Privacy by Default Preferences - Experiment and Analysis., , , and . ICISSP, page 53-62. SciTePress, (2016)Systematizing the State of Knowledge in Detecting Privacy Sensitive Information in Unstructured Texts using Machine Learning., , , and . PST, page 1-7. IEEE, (2023)Enhancing Privacy in Federated Learning with Local Differential Privacy for Email Classification., , and . DPM/CBT@ESORICS, volume 13619 of Lecture Notes in Computer Science, page 3-18. Springer, (2022)