On the Security and Feasibility of Safebook: A Distributed Privacy-Preserving Online Social Network

被引:0
|
作者
Cutillo, Leucio Antonio [1 ]
Molva, Refik [1 ]
Strufe, Thorsten [2 ]
机构
[1] EURECOM, Sophia Antipolis, France
[2] Tech Univ Darmstadt, Darmstadt, Germany
来源
关键词
D O I
暂无
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
Safebook tackles the security and privacy problems of online social networks. It puts a special emphasis on the privacy of users with respect to the application provider and provides defenses against intruders or malicious users. In order to assure privacy in the face of potential violations by the provider, Safebook is designed in a decentralized architecture. It relies on the cooperation among the independent parties that represent the users of the online social network at the same time. Safebook addresses the problem of building secure and privacy-preserving data storage and communication mechanisms in a peer-to-peer system by leveraging trust relationships akin to social networks in real life. This paper resumes the contributions of [7,9,8], and extends the first performance and security evaluation of Safebook.
引用
收藏
页码:86 / +
页数:2
相关论文
共 50 条
  • [21] A Privacy-Preserving Scheme for Online Social Networks with Efficient Revocation
    Sun, Jinyuan
    Zhu, Xiaoyan
    Fang, Yuguang
    2010 PROCEEDINGS IEEE INFOCOM, 2010,
  • [22] A privacy-preserving algorithm for distributed training of neural network ensembles
    Yuan Zhang
    Sheng Zhong
    Neural Computing and Applications, 2013, 22 : 269 - 282
  • [23] A Privacy-Preserving Friend Recommendation Mechanism for Online Social Networks
    Liu, Fukang
    Wu, Guorui
    Liu, Yang
    2020 4TH INTERNATIONAL CONFERENCE ON CRYPTOGRAPHY, SECURITY AND PRIVACY (ICCSP 2020), 2020, : 63 - 67
  • [24] Efficient privacy-preserving content recommendation for online social communities
    Li, Dongsheng
    Lv, Qin
    Shang, Li
    Gu, Ning
    NEUROCOMPUTING, 2017, 219 : 440 - 454
  • [25] Privacy-Preserving Data Allocation in Decentralized Online Social Networks
    De Salve, Andrea
    Mori, Paolo
    Ricci, Laura
    Al-Aaridhi, Raed
    Graffi, Kalman
    DISTRIBUTED APPLICATIONS AND INTEROPERABLE SYSTEMS, DAIS 2016, 2016, 9687 : 47 - 60
  • [26] Towards Privacy-Preserving Content Sharing for Online Social Networks
    Phithakkitnukoon, Santi
    PROCEEDINGS OF THE 2018 ACM INTERNATIONAL JOINT CONFERENCE ON PERVASIVE AND UBIQUITOUS COMPUTING AND PROCEEDINGS OF THE 2018 ACM INTERNATIONAL SYMPOSIUM ON WEARABLE COMPUTERS (UBICOMP/ISWC'18 ADJUNCT), 2018, : 1088 - 1095
  • [27] Privacy-preserving Bayesian network learning on distributed heterogeneous data
    Wang, Hong-Mei
    Zeng, Yuan
    Zhao, Zheng
    Wang, Cheng-Shan
    Tianjin Daxue Xuebao (Ziran Kexue yu Gongcheng Jishu Ban)/Journal of Tianjin University Science and Technology, 2007, 40 (09): : 1025 - 1028
  • [28] A Distributed Privacy-Preserving Learning Dynamics in General Social Networks
    Tao, Youming
    Chen, Shuzhen
    Li, Feng
    Yu, Dongxiao
    Yu, Jiguo
    Sheng, Hao
    IEEE TRANSACTIONS ON KNOWLEDGE AND DATA ENGINEERING, 2023, 35 (09) : 9547 - 9561
  • [29] A privacy-preserving friend recommendation scheme in online social networks
    Zhang, Shiwen
    Li, Xiong
    Liu, Haowen
    Lin, Yaping
    Sangaiah, Arun Kumar
    SUSTAINABLE CITIES AND SOCIETY, 2018, 38 : 275 - 285
  • [30] A privacy-preserving algorithm for distributed training of neural network ensembles
    Zhang, Yuan
    Zhong, Sheng
    NEURAL COMPUTING & APPLICATIONS, 2013, 22 : S269 - S282