Abstract
Social network contains the interaction between social members, which constitutes the structure and attribute of social network. The interactive relationship of social network contains a lot of personal privacy information. The direct release of social network data will cause the disclosure of privacy information. Aiming at the dynamic characteristics of social network data release, a new dynamic social network data publishing method based on differential privacy was proposed. This method was consistent with differential privacy. It is named DDPA (Dynamic Differential Privacy Algorithm). DDPA algorithm is an improvement of privacy protection algorithm in static social network data publishing. DDPA adds noise which follows Laplace to network edge weights. DDPA identifies the edge weight information that changes as the number of iterations increases, adding the privacy protection budget. Through experiments on real data sets, the results show that the DDPA algorithm satisfies the user’s privacy requirement in social network. DDPA reduces the execution time brought by iterations and reduces the information loss rate of graph structure.
Highlights
The innovation of the knowledge society has promoted the advent of the era of “Internet +”, such as medical data, big data of intelligent city and large education data, which lead the trend of Internet changes
DDPA algorithm is an improvement of privacy protection algorithm in static social network data publishing
This paper presents the method of data privacy protection which can be applied to the dynamic social network better; 2) In this paper, a strict differential privacy preserving model is introduced
Summary
The innovation of the knowledge society has promoted the advent of the era of “Internet +”, such as medical data, big data of intelligent city and large education data, which lead the trend of Internet changes. Social network is a new application mode under the Internet background, and the data dissemination in social. The user’s large number of personal privacy information may be leaked when social network data is analyzed and excavated. Social networks are evolving and changing that named dynamic social networks. The privacy strategy of the static social network data release usually cannot adapt to the dynamic development of social network efficiently. It has far-reaching theoretical significance and practical value in the field of information security and network space security. The social network privacy protection method mainly studies the static social network data dissemination
Sign-in/Register to view highlights & summary Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
