社交网络基于邻居结点亲密度的信息流控制

Web2.0技术的快速发展推动在线社交网络成为人们传播信息最流行的平台。用户在发布海量数据带来巨大的商业价值的同时,隐私信息泄露问题也随之而来。针对在线社交网络中隐私信息流不可控制的问题,提出了基于邻居结点亲密度的信息流控制模型。该模型通过计算用户授予好友可访问资源的敏感度来衡量邻居结点的亲密关系,并利用用户与好友之间的共同邻居数量对模型进行改进。此外,借鉴多级安全等级(MLS)的思想,将传递信息进行亲密度安全等级划分。社交网络管理者通过对传递信息设置合理的亲密度范围,以实现隐私信息流可控制范围内的传递。最后,通过仿真实验进行参数调整,验证了该模型的有效性和实用性。

Based on neighbor node intimacy for the information flow control model and application in online social network

The rapid development of Web2.0 technology promotes the online social network which is becoming the most popular platform for people to spread information. The huge amount of data released by users brings huge commercial value and privacy information disclosure. To solve the problem that the privacy information flow cannot be controlled in online social network, an information flow control model based on neighbor node intimacy is proposed. By computing the sensitivity of resources that users allow their friends to access, the model measures the intimacy relationship of neighbor nodes. And the number of common neighbors between users and their friends can be used to improve the model. In addition, information is divided into different intimacy security levels by referring to the ideas of the level of multilevel security (MLS). By setting reasonable scope of intimacy to convey information, social network managers may control the privacy information flow within a certain scope. The simulation experiments with parameter adjusting demonstrate the validity and practicability of the proposed model.