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保護私有信息的社交網絡合群判定

Privacy-preserving join decision in social networks

  • 摘要: 為了解決社交網絡中用戶申請加入群組的合適性判斷問題,將安全多方計算技術中的求和協議與秘密比較協議相結合提出了保護私有信息的合群判定協議.其中基礎協議解決一維線性模型下問題的安全求解,擴展協議對基于圓邊界的多維模型情況進行判定.針對單一申請者與網絡群組多用戶的特點,將問題轉換為兩方計算模型可實現的形式,在證明了協議正確性的基礎上分析協議的復雜度,并且利用安全視圖的方法逐步驗證了在協議執行過程中不會泄露任何個人的隱私數據.實際使用中協議能夠有效地回避盲目的系統推薦和管理員離線所產生的判定時延,同時保護申請者和群組成員的隱私數據.

     

    Abstract: In order to decide the appropriateness of a new user applying to join in a group in the social network, a privacy-preserving protocol was designed by the secure sum protocol and secure comparison protocol. In the privacy-preserving protocol, the secure basis protocol was devised for problems under a one-dimensional linear model, and the advanced protocol for a multi-dimensional model with a circular boundary. For the case of a single applicant and a multi-user group, the solution was converted and realized in a two-party computation model. After the proof of correctness, the complexity was discussed, and there is no leaking message during the process by the analysis of data views in each step. The privacy-preserving protocol avoids not only the blindness of auto recommendation by the net-system but also the decision delay due to the administrator's offline. In the meanwhile, the privacy of the applicant and group members can be protected without leaking any information.

     

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