Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social Media
On social platforms like Facebook, it is popular and pleasurable to share photos among friends, but it also puts other participants in the same picture in jeopardy when the photos are released online without the permission from them. To solve this problem, recently, the researchers have designed som...
| Main Authors: | , , , , , |
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| Format: | Article |
| Language: | English |
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IEEE
2019-01-01
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| Series: | IEEE Access |
| Subjects: | |
| Online Access: | https://ieeexplore.ieee.org/document/8731971/ |
| _version_ | 1830299387941617664 |
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| author | Lihong Tang Wanlun Ma Marthie Grobler Weizhi Meng Yu Wang Sheng Wen |
| author_facet | Lihong Tang Wanlun Ma Marthie Grobler Weizhi Meng Yu Wang Sheng Wen |
| author_sort | Lihong Tang |
| collection | DOAJ |
| description | On social platforms like Facebook, it is popular and pleasurable to share photos among friends, but it also puts other participants in the same picture in jeopardy when the photos are released online without the permission from them. To solve this problem, recently, the researchers have designed some fine-grained access control mechanisms for photos shared on the social platform. The uploader will tag each participant in the photo, then they will receive internal messages and configure their own privacy control strategies. These methods protect their privacy in photos by blurring out the faces of participants. However, there is still some defect in these strategies due to the unpredictable tagging behaviors of the uploader. Malicious users can easily manipulate unauthorized tagging processes and then publish the photos, which the participants want them to be confidential in social media. To address this critical problem, we propose a participant-free tagging system for photos on social platforms. This system excludes potential adversaries through automatic tagging processes over two cascading stages: 1) an initialization stage will be applied to every new user to collect his/her own portrait samples for future internal searching and tagging, and; 2) the remaining unidentified participants will be tagged in cooperative tagging stage by the users who have been identified in the first stage. For the system evaluation of efficiency and effectiveness, we conducted a series of experiments. The results demonstrated the tagging efficiency (96% tagging rate and 0.77s/photo tagging speed on average), photo masking and unmasking efficiency (0.13s/face on average), and the privacy preserving performance (over 90% identities in both group and individual photo are preserved). |
| first_indexed | 2024-12-19T08:07:24Z |
| format | Article |
| id | doaj.art-dc4f14c9f6e34c70975d63ac9ade2d42 |
| institution | Directory Open Access Journal |
| issn | 2169-3536 |
| language | English |
| last_indexed | 2024-12-19T08:07:24Z |
| publishDate | 2019-01-01 |
| publisher | IEEE |
| record_format | Article |
| series | IEEE Access |
| spelling | doaj.art-dc4f14c9f6e34c70975d63ac9ade2d422022-12-21T20:29:43ZengIEEEIEEE Access2169-35362019-01-017755567556710.1109/ACCESS.2019.29210298731971Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social MediaLihong Tang0Wanlun Ma1Marthie Grobler2https://orcid.org/0000-0001-6933-0145Weizhi Meng3Yu Wang4https://orcid.org/0000-0002-9807-2293Sheng Wen5School of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, ChinaDepartment of Information and Communication Engineering, University of Electronic Science and Technology of China, Chengdu, ChinaData61, CSIRO, Melbourne, VIC, AustraliaDepartment of Applied Mathematics and Computer Science, Technical University of Denmark, Kongens Lyngby, DenmarkSchool of Computer Science and Cyber Engineering, Guangzhou University, Guangzhou, ChinaSchool of Software and Electrical Engineering, Swinburne University of Technology, Melbourne, VIC, AustraliaOn social platforms like Facebook, it is popular and pleasurable to share photos among friends, but it also puts other participants in the same picture in jeopardy when the photos are released online without the permission from them. To solve this problem, recently, the researchers have designed some fine-grained access control mechanisms for photos shared on the social platform. The uploader will tag each participant in the photo, then they will receive internal messages and configure their own privacy control strategies. These methods protect their privacy in photos by blurring out the faces of participants. However, there is still some defect in these strategies due to the unpredictable tagging behaviors of the uploader. Malicious users can easily manipulate unauthorized tagging processes and then publish the photos, which the participants want them to be confidential in social media. To address this critical problem, we propose a participant-free tagging system for photos on social platforms. This system excludes potential adversaries through automatic tagging processes over two cascading stages: 1) an initialization stage will be applied to every new user to collect his/her own portrait samples for future internal searching and tagging, and; 2) the remaining unidentified participants will be tagged in cooperative tagging stage by the users who have been identified in the first stage. For the system evaluation of efficiency and effectiveness, we conducted a series of experiments. The results demonstrated the tagging efficiency (96% tagging rate and 0.77s/photo tagging speed on average), photo masking and unmasking efficiency (0.13s/face on average), and the privacy preserving performance (over 90% identities in both group and individual photo are preserved).https://ieeexplore.ieee.org/document/8731971/Social mediaface taggingprivacy protectionsystem security |
| spellingShingle | Lihong Tang Wanlun Ma Marthie Grobler Weizhi Meng Yu Wang Sheng Wen Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social Media IEEE Access Social media face tagging privacy protection system security |
| title | Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social Media |
| title_full | Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social Media |
| title_fullStr | Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social Media |
| title_full_unstemmed | Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social Media |
| title_short | Faces are Protected as Privacy: An Automatic Tagging Framework Against Unpermitted Photo Sharing in Social Media |
| title_sort | faces are protected as privacy an automatic tagging framework against unpermitted photo sharing in social media |
| topic | Social media face tagging privacy protection system security |
| url | https://ieeexplore.ieee.org/document/8731971/ |
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