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基于節點分割的社交網絡屬性隱私保護

軟件學報ISSN 1000-9825, CODEN RUXUEW E-mail: [email protected]://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html

Journal of Software,2014,25(4):768?780 [doi: 10.13328/http://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html ki.jos.004565] http://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html

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基于節點分割的社交網絡屬性隱私保護

付艷艷1, 張敏1, 馮登國1, 陳開渠2

1(中國科學院軟件研究所可信計算與信息保證實驗室,北京 100190)

2(國家超級計算深圳中心(深圳云計算中心),廣東深圳 518055)

通訊作者: 付艷艷, E-mail: [email protected]://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html , http://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html

摘要: 現有研究表明,社交網絡中用戶的社交結構信息和非敏感屬性信息均會增加用戶隱私屬性泄露的風險.

針對當前社交網絡隱私屬性匿名算法中存在的缺乏合理模型、屬性分布特征擾動大、忽視社交結構和非敏感屬性

對敏感屬性分布的影響等弱點,提出一種基于節點分割的隱私屬性匿名算法.該算法通過分割節點的屬性連接和社

交連接,提高了節點的匿名性,降低了用戶隱私屬性泄露的風險.此外,量化了社交結構信息對屬性分布的影響,根據

屬性相關程度進行節點的屬性分割,能夠很好地保持屬性分布特征,保證數據可用性.實驗結果表明,該算法能夠在

保證數據可用性的同時,有效抵抗隱私屬性泄露.

關鍵詞: 社交網絡;屬性隱私;匿名;節點分割

中圖法分類號: TP309文獻標識碼: A

中文引用格式: 付艷艷,張敏,馮登國,陳開渠.基于節點分割的社交網絡屬性隱私保護.軟件學報,2014,25(4):768?780.

http://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html /1000-9825/4565.htm

英文引用格式: Fu YY, Zhang M, Feng DG, Chen KQ. Attribute privacy preservation in social networks based on node anatomy.

Ruan Jian Xue Bao/Journal of Software, 2014,25(4):768?780 (in Chinese).http://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html /1000-9825/4565.htm

Attribute Privacy Preservation in Social Networks Based on Node Anatomy

FU Yan-Yan1, ZHANG Min1, FENG Deng-Guo1, CHEN Kai-Qu2

1(Laboratory of TCA, Institute of Software, The Chinese Academy of Sciences, Beijing 100190, China)

2(National Supercomputing Center in Shenzhen (Shenzhen Cloud Computing Center), Shenzhen 518055, China)

Corresponding author: FU Yan-Yan, E-mail: [email protected]://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html , http://www.fdwufp.live/doc/b491c38b5022aaea998f0f7d.html

Abstract: Recent research shows that social structures or non-sensitive attributes of users can increase risks of user sensitive attribute

disclosure in social networks. Most of the existing private attribute anonymization schemes have many defects, such as lack of proper

model, too much distortion on attributes distribution, neglect social structure and non-sensitive attributes’ influence on sensitive attributes.

In this paper, an attribute privacy preservation scheme based on node anatomy is proposed. It allocates original node’s attribute links and

social links to new nodes to improve original node’s anonymity, thus protects user from sensitive attribute disclosure. Meanwhile, it

measures social structure influence on attribute distribution, and splits attributes according to attributes’ correlations. Experimental results

show that the proposed scheme can maintain high data utility and resist private attribute disclosure.

Key words: social netwo
rk; attribute privacy; anonymity; node anatomy

Key words: social network; attribute privacy; anonymity; node anatomy

隨著社交網絡(social network,簡稱SNS)的日益發展,越來越多的個人信息被網絡記錄儲存下來.用戶主動

或者被動提交的好友互動記錄、興趣愛好標簽、簽到信息、消費記錄等包含了大量社交結構信息和屬性信息,

為定向廣告、推薦系統等應用提供了豐富的數據來源.用戶的需求、喜好、屬性、行為以及可能具有的關系等,

能夠被盡可能詳細地加以刻畫[1?3].但是,隨著用戶網絡形象的進一步豐富,能夠用于確定用戶真實身份的信息

?基金項目: 國家自然科學基金(61232005, 61100237); 深圳市戰略新興產業發展專項資金(CXZZ20120831113048965)

收稿時間:2013-09-10; 定稿時間: 2013-12-18

基于節點分割的社交網絡屬性隱私保護

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