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A research on hierarchical trackback technique for individual big data

机译:个别大数据的分层载体技术研究

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In order to solve the privacy protection problem of individual big data, this paper proposes a hierarchical data trackback technique (HDTT). This technique can realise the data trackback through inter-domain and intra-domain path reconstruction without increasing the core network storage load. The main method is as follows: record the AS domain involved by data packets and IP address information with GBF data structure by use of idle part of packet header, determine the AS domain first with GBFAS data during the path reconstruction, and then determine the intra-domain router with GBFIP data to complete the data trackback. Finally, through the verification of Data Collect Treasure platform by project group, the contact ratio between inter-domain and intra-domain paths is up to over 98% and 92%, respectively, so HDTT technique can accurately reconstruct the data flow path, realise the data trackback and achieve the privacy protection of individual big data.
机译:为了解决个体大数据的隐私保护问题,本文提出了分层数据追踪技术(HDTT)。 该技术可以通过域间和域路径重建来实现数据载覆,而无需增加核心网络存储负载。 主要方法如下:通过使用空闲部分的数据包标题与GBF数据结构涉及的作为数据包和IP地址信息录制的域,在路径重建期间使用GBFA数据确定作为域,然后确定帧内 - 具有GBFIP数据的DOMAIN路由器,以完成数据载销。 最后,通过验证项目组数据收集宝平台,域间和域路径之间的接触比分别超过98%和92%,因此HDTT技术可以准确地重建数据流路径,实现数据流路径 数据追踪并实现个人大数据的隐私保护。

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