Privacy-Preserving Blockchain-Based Nonlinear SVM Classifier Training for Social Networks
Joint Authors
Source
Security and Communication Networks
Issue
Vol. 2020, Issue 2020 (31 Dec. 2020), pp.1-10, 10 p.
Publisher
Hindawi Publishing Corporation
Publication Date
2020-12-14
Country of Publication
Egypt
No. of Pages
10
Main Subjects
Information Technology and Computer Science
Abstract EN
With the development of social networks, there are more and more social data produced, which usually contain valuable knowledge that can be utilized in many fields, such as commodity recommendation and sentimental analysis.
The SVM classifier, as one of the most prevailing machine learning techniques for classification, is a crucial tool for social data analysis.
Since training a high-quality SVM classifier usually requires a huge amount of data, it is a better choice for individuals and small enterprises to conduct collaborative training with multiple parties.
Nevertheless, it causes privacy risks when sharing sensitive data with untrusted people and enterprises.
Existing solutions mainly adopt the computation-intensive cryptographic methods which are not efficient for practical applications.
Therefore, it is an urgent and challenging task to realize efficient SVM classifier training while protecting privacy.
In this paper, we propose a novel privacy-preserving nonlinear SVM classifier training scheme based on blockchain.
We first design a series of secure computation protocols which can achieve secure nonlinear SVM classifier training with minimal computation overheads.
Then, leveraging these building blocks, we propose a blockchain-based secure nonlinear SVM classifier training scheme that realizes collaborative training while protecting privacy.
We conduct a thorough analysis of the security properties of our scheme.
Experiments over a real dataset show that our scheme achieves high accuracy and practical efficiency.
American Psychological Association (APA)
Jia, Nan& Fu, Shaojing& Xu, Ming. 2020. Privacy-Preserving Blockchain-Based Nonlinear SVM Classifier Training for Social Networks. Security and Communication Networks،Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1208823
Modern Language Association (MLA)
Jia, Nan…[et al.]. Privacy-Preserving Blockchain-Based Nonlinear SVM Classifier Training for Social Networks. Security and Communication Networks No. 2020 (2020), pp.1-10.
https://search.emarefa.net/detail/BIM-1208823
American Medical Association (AMA)
Jia, Nan& Fu, Shaojing& Xu, Ming. Privacy-Preserving Blockchain-Based Nonlinear SVM Classifier Training for Social Networks. Security and Communication Networks. 2020. Vol. 2020, no. 2020, pp.1-10.
https://search.emarefa.net/detail/BIM-1208823
Data Type
Journal Articles
Language
English
Notes
Includes bibliographical references
Record ID
BIM-1208823