This is a dataset for research on privacy protection in context-dependent photo sharing, in our paper titled “Context-Dependent Privacy-Aware Photo Sharing based on Machine Learning”. The dataset was created through a user study on on 20 subjects, containing 12’216 personalized context-dependent sharing decisions for 1’018 images. The dataset can be helpful for related research of privacy protection or prediction in photo or information sharing, particularly in a context-dependent scenario. More information about the paper can be found in the paper (https://link.springer.com/chapter/10.1007/978-3-319-58469-0_7 or https://infoscience.epfl.ch/record/226368). For privacy issue, we cannot release the images directly. Instead, all annotated information of those images, context information and users’ sharing decisions are provided in the dataset.
Get the dataset easily by downloading the file via the Link to Dataset.
Permission is hereby granted, without written agreement and without license or royalty fees, to use, copy, modify, and distribute the data provided and its documentation for research purpose only. The data provided may not be commercially distributed. In no event shall the Ecole Polytechnique Fédérale de Lausanne (EPFL) be liable to any party for direct, indirect, special, incidental, or consequential damages arising out of the use of the data and its documentation. The Ecole Polytechnique Fédérale de Lausanne (EPFL) specifically disclaims any warranties. The data provided hereunder is on an “as is” basis and the Ecole Polytechnique Fédérale de Lausanne (EPFL) has no obligation to provide maintenance, support, updates, enhancements, or modifications.
If you use these database in your research we kindly ask you to reference the associated paper:
Yuan, L., Theytaz, J.R., Ebrahimi, T.: ‘Context-dependent privacy-aware photo sharing based on machine learning’. Proc. of 32nd Int. Conf. ICT Systems Security and Privacy Protection (IFIP SEC 2017), 2017
Should you have any questions regarding this research please contact Lin Yuan (linyuan8966 (at) gmail.com) or Touradj Ebrahimi (touradj.ebrahimi (at) epfl.ch)