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首页> 外文期刊>Future generation computer systems >Towards an asynchronous aggregation-capable watermark for end-to-end protection of big data streams
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Towards an asynchronous aggregation-capable watermark for end-to-end protection of big data streams

机译：迈向具有异步聚合功能的水印，以对大数据流进行端到端保护

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We consider how an untrusted data aggregator can be assessed over multiple data streams. The aggregator could be the sink node in a sensor network where all the sensory data are gathered, or a smart-meter responsible for computing power measurements of a group of households, or any other entity that is basically in charge of answering aggregation queries such as average or summation in a data streaming environment. In these applications, important decisions are made based on the aggregated results and therefore, it is vitally important to investigate the authenticity and integrity of aggregated values. One possible approach for solving this problem is marking the data before sending it out to the aggregators (i.e. marked at the point of origin) such that the existence of those marks could be verified subsequently after the aggregation process. Our goal is to produce hidden marks that remain detectable after the aggregation and thereby not only the trustworthiness of every individual data source, but also the trustworthiness of the aggregators could be verified. This problem is referred to secure data aggregation that has been investigated by means of digital watermarking and steganography techniques in recent years. Data synchronization is a serious problem which was not addressed in the current schemes, though. Therefore, in this paper, a new watermarking construction is proposed that provides 'synchronization marks' in the aggregated data stream and helps protect the data itself at the end-points. Our method works at the data layer so standard transport layer security methods can be used to protect the transport of data if it is required. Finally, a set of experiments are conducted using synthesized and real sensory data as a proof of concept.
机译：我们考虑如何在多个数据流上评估不可信的数据聚合器。聚合器可以是收集所有传感数据的传感器网络中的汇聚节点，也可以是负责计算一组家庭的功率测量的智能电表，或者是基本上负责回答聚合查询的任何其他实体，例如数据流环境中的平均值或求和。在这些应用程序中，基于汇总结果做出重要决策，因此，调查汇总值的真实性和完整性至关重要。解决该问题的一种可能方法是在将数据发送到聚合器之前对其进行标记（即在原始点标记），以便可以在聚合过程之后随后验证这些标记的存在。我们的目标是产生在聚合之后仍可检测到的隐藏标记，从而不仅可以验证每个单独数据源的可信度，而且可以验证聚合器的可信度。这个问题被称为安全数据聚合，近年来已经通过数字水印和隐写技术进行了研究。数据同步是一个严重的问题，但是当前方案并未解决。因此，在本文中，提出了一种新的水印构造，该构造在聚合的数据流中提供“同步标记”，并有助于在端点保护数据本身。我们的方法适用于数据层，因此如果需要，可以使用标准的传输层安全性方法来保护数据的传输。最后，使用合成的真实感官数据作为概念证明进行了一组实验。

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