TY - JOUR
T1 - How to Prevent Social Media Platforms From Knowing the Images You Share With Friends
AU - Li, Dawei
AU - Guo, Yuxiao
AU - Liu, Di
AU - Liu, Qifan
AU - Bian, Song
AU - Guan, Zhenyu
N1 - Publisher Copyright:
© 2002-2012 IEEE.
PY - 2025
Y1 - 2025
N2 - The surge in image sharing on social media platforms escalates private information extraction for commercial use, increasing user demand for privacy protection. However, the dynamics of group communication within online social networks and the image compression imposed by platforms present significant challenges to secure key exchange and reliable image sharing in existing solutions. In this paper, we propose PrivSocial to prevent social media platforms from extracting private information in images shared within group communications. Specifically, we propose two frameworks, a server-based framework and a subscription-based framework, making PrivSocial applicable to different social media platforms and providing users with optional security levels, enhancing the flexibility and efficiency. To achieve intra-group key agreement and ensure image privacy protection, both frameworks integrate optimized continuous group key agreement and a novel image encryption scheme resisting compression. We implement an Android-based Priv-raster application and deploy a prototype on Twitter. Furthermore, we evaluate the proposed encryption scheme, and experimental results show that it has efficient encryption and decryption performance while being resistant to jigsaw puzzle solver attacks. The multi-user simulation experiments also demonstrate that the processing time of a single user is mere milliseconds, and the scheme can efficiently support tens of thousands of groups.
AB - The surge in image sharing on social media platforms escalates private information extraction for commercial use, increasing user demand for privacy protection. However, the dynamics of group communication within online social networks and the image compression imposed by platforms present significant challenges to secure key exchange and reliable image sharing in existing solutions. In this paper, we propose PrivSocial to prevent social media platforms from extracting private information in images shared within group communications. Specifically, we propose two frameworks, a server-based framework and a subscription-based framework, making PrivSocial applicable to different social media platforms and providing users with optional security levels, enhancing the flexibility and efficiency. To achieve intra-group key agreement and ensure image privacy protection, both frameworks integrate optimized continuous group key agreement and a novel image encryption scheme resisting compression. We implement an Android-based Priv-raster application and deploy a prototype on Twitter. Furthermore, we evaluate the proposed encryption scheme, and experimental results show that it has efficient encryption and decryption performance while being resistant to jigsaw puzzle solver attacks. The multi-user simulation experiments also demonstrate that the processing time of a single user is mere milliseconds, and the scheme can efficiently support tens of thousands of groups.
KW - Online social networks
KW - encryption-then-compression system
KW - privacy protection
KW - semi-trusted platforms
UR - https://www.scopus.com/pages/publications/85217499948
U2 - 10.1109/TMC.2025.3538885
DO - 10.1109/TMC.2025.3538885
M3 - 文章
AN - SCOPUS:85217499948
SN - 1536-1233
VL - 24
SP - 5808
EP - 5823
JO - IEEE Transactions on Mobile Computing
JF - IEEE Transactions on Mobile Computing
IS - 7
ER -