A two-party privacy preserving set intersection protocol against malicious users in cloud computing

2017 ◽  
Vol 54 ◽  
pp. 41-45 ◽  
Author(s):  
Xuefei Cao ◽  
Hui Li ◽  
Lanjun Dang ◽  
Yin Lin
Keyword(s):  
Cloud Computing ◽  
Privacy Preserving ◽  
Set Intersection

scholarly journals Outsourcing Set Intersection Computation Based on Bloom Filter for Privacy Preservation in Multimedia Processing

2018 ◽  
Vol 2018 ◽  
pp. 1-12 ◽  
Author(s):  
Hongliang Zhu ◽  
Meiqi Chen ◽  
Maohua Sun ◽  
Xin Liao ◽  
Lei Hu
Keyword(s):  
Cloud Computing ◽  
Homomorphic Encryption ◽  
Low Cost ◽  
Bloom Filter ◽  
Privacy Preserving ◽  
Cloud Services ◽  
Multimedia Application ◽  
Computation Method ◽  
Multimedia Processing ◽  
Set Intersection

With the development of cloud computing, the advantages of low cost and high computation ability meet the demands of complicated computation of multimedia processing. Outsourcing computation of cloud could enable users with limited computing resources to store and process distributed multimedia application data without installing multimedia application software in local computer terminals, but the main problem is how to protect the security of user data in untrusted public cloud services. In recent years, the privacy-preserving outsourcing computation is one of the most common methods to solve the security problems of cloud computing. However, the existing computation cannot meet the needs for the large number of nodes and the dynamic topologies. In this paper, we introduce a novel privacy-preserving outsourcing computation method which combines GM homomorphic encryption scheme and Bloom filter together to solve this problem and propose a new privacy-preserving outsourcing set intersection computation protocol. Results show that the new protocol resolves the privacy-preserving outsourcing set intersection computation problem without increasing the complexity and the false positive probability. Besides, the number of participants, the size of input secret sets, and the online time of participants are not limited.

An Efficient Privacy-Preserving Rank Query over Encrypted Data in Cloud Computing

2012 ◽  
Vol 35 (11) ◽  
pp. 2215 ◽  
Author(s):  
Fang-Quan CHENG ◽  
Zhi-Yong PENG ◽  
Wei SONG ◽  
Shu-Lin WANG ◽  
Yi-Hui CUI
Keyword(s):  
Cloud Computing ◽  
Privacy Preserving ◽  
Encrypted Data

Privacy-preserving cloud computing on sensitive data: A survey of methods, products and challenges

2019 ◽  
Vol 140-141 ◽  
pp. 38-60 ◽  
Author(s):  
Josep Domingo-Ferrer ◽  
Oriol Farràs ◽  
Jordi Ribes-González ◽  
David Sánchez
Keyword(s):  
Cloud Computing ◽  
Privacy Preserving ◽  
Sensitive Data

Multi-key privacy-preserving deep learning in cloud computing

2017 ◽  
Vol 74 ◽  
pp. 76-85 ◽  
Author(s):  
Ping Li ◽  
Jin Li ◽  
Zhengan Huang ◽  
Tong Li ◽  
Chong-Zhi Gao ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Deep Learning ◽  
Privacy Preserving

Privacy-preserving public auditing for secure data storage in fog-to-cloud computing

2019 ◽  
Vol 127 ◽  
pp. 59-69 ◽  
Author(s):  
Hui Tian ◽  
Fulin Nan ◽  
Chin-Chen Chang ◽  
Yongfeng Huang ◽  
Jing Lu ◽  
...  
Keyword(s):  
Cloud Computing ◽  
Data Storage ◽  
Privacy Preserving ◽  
Public Auditing ◽  
Secure Data
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