基于异步信息的匿名移动数据集的用户身份识别

Identifying User's ID from Anonymous Mobility Trace Set via Asynchronous Side Information

为了保护用户的隐私,大部分公开数据集都采用隐藏真实ID和引入噪声信息的方法来进行匿名处理。这些匿名处理即使在异步参考信息的攻击下也是脆弱的:即使只有部分位置信息暴露给攻击者并且暴露信息和公开数据集的收集过程不在同一时段内,攻击者依然能够识别出节点在公开数据集中的身份。首先,实验证明已有算法在异步信息情况下不适用;然后,提出针对异步信息的热点矩阵算法。采用3个真实移动数据集验证了识别算法的准确率。实验证明,热点矩阵法在异步信息条件下能够取得远高于已有方法的准确率。

With the development of social network applications,and to meet the demand of mobile system designing and scientific research, plenty of location trace information has been collected and published. Most public traces utilize the a- nonymous ID and adding noise to protect the privacy of users. However, these processes are vulnerable when facing a- synchronous attack. Even if partial information was exposed to adversary and the collections of side information and public trace set are not in the same duration, the adversary can also identify user＇s ID with high accuracy. Our experi- ment shows that the existing method is not applicable when facing asynchronous side information. A novel method ap- plicable in asynchronous condition was proposed which is called hot-matrix method. To verify this method, we employed experiments in three different mobility trace sets, whose subject is taxi, bus and human beings respectively. Experiments show that hot-matrix method performs much better than existing approach.