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- Title
Rule Fusion of Privacy Protection Strategies for Co-Ownership Data Sharing.
- Authors
Ma, Tinghuai; Su, Yuming; Rong, Huan; Qian, Yurong; Al-Nabhan, Najla
- Abstract
With the rapid development of social networks, personal privacy leakage has become more and more serious. A social network is a shared platform. Resources in a social network may be shared by multiple owners. In order to prevent privacy leakage, each owner assigns a corresponding privacy protection strategy. For the same shared contents, integrating the privacy protection strategies of all owners is the key problem for sharing. This paper proposes a rule fusion method of privacy protection for the co-ownership of data shared in social networks. First, the content of the protection is defined according to different privacy requirements. Second, this paper uses predicate logic formulas to abstract the natural language-based description of privacy protection and further provides a logical model of privacy protection rules. Third, this paper gives the definition of privacy protection heterogeneous rules and provides a rule fusion algorithm to ensure no conflict exists among these rules. The experimental results show that the proposed rule-based fusion method of privacy protection strategy performs at a higher level than the privacy protection strategy fusion.
- Subjects
INFORMATION sharing; PRIVACY; DATA security failures; PREDICATE (Logic); SOCIAL networks
- Publication
Mathematics (2227-7390), 2022, Vol 10, Issue 6, p969
- ISSN
2227-7390
- Publication type
Article
- DOI
10.3390/math10060969