摘要：

為解決直接發(fā)布社會網(wǎng)絡(luò)會侵害個(gè)體隱私，進(jìn)而需要進(jìn)行隱私保護(hù)的問題，針對擁有社會個(gè)體鄰域信息作為背景知識進(jìn)行敏感邊識別攻擊的應(yīng)用場景，提出了（k, 2）-匿名發(fā)布的隱私保護(hù)方法。該方法通過對原始社會網(wǎng)絡(luò)圖進(jìn)行最小結(jié)構(gòu)修改，實(shí)現(xiàn)最大的數(shù)據(jù)效用，設(shè)計(jì)實(shí)現(xiàn)了滿足隱私保護(hù)要求的匿名發(fā)布算法，并在數(shù)據(jù)集上進(jìn)行了驗(yàn)證。實(shí)驗(yàn)結(jié)果表明，該方法能有效抵御敏感邊的識別攻擊，獲得可接受的發(fā)布質(zhì)量。

關(guān)鍵詞: 社會網(wǎng)絡(luò), 隱私保護(hù), 敏感邊, 匿名發(fā)布

Abstract:

Individual privacy can be breached if social networks are released directly. So privacy protection should be carried on. The privacy protection method named (k,2)-anonymity publication is proposed. The method is suitable for the scene that the aggressor with background knowledge of neighborhood information wants to identify sensitive edges in published social networks. The minimum structural modification is performed on origin social networks graphs and the largest amount of information from the published networks is obtained. Design and implement the algorithm meeting privacy preservation requirements of the published anonymously and carry on experiment on dataset to validate. Experimental results show that the method can effectively resist the sensitive edges identify attack and get acceptable release quality.

Key words: LAN Li-hui1,2, SUN Ying-hui1, JU Shi-guang2

中圖分類號: 

引用本文

蘭麗輝, 孫英慧, 鞠時(shí)光. 社會網(wǎng)絡(luò)發(fā)布中敏感邊的隱私保護(hù)[J]. J4, 2011, 29(4): 323-330.

LAN Li-Hui, SUN Yang-Hui, JU Shi-Guang. Privacy Preservation of Sensitive Edges in Social Networks Publication[J]. J4, 2011, 29(4): 323-330.

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