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In the shadows we trust: A secure aggregation tolerant watermark for data streams

机译:在我们的阴影下,我们相信:数据流的安全聚合容忍水印

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In many applications such as sensor networks, e-healthcare and environmental monitoring, data is continuously streamed and combined from multiple resources in order to make decisions based on the aggregated data streams. One major concern in these applications is assuring high trustworthiness of the aggregated data stream for correct decision-making. For example, an adversary may compromise a few data-sources and introduce false data into the aggregated data-stream and cause catastrophic consequences. In this work, we propose a novel method for verifying data integrity by embedding several signature codes within data streams known as digital watermarking. Therefore, the integrity of the data streams can be verified by decoding the embedded signatures even as the data go through multiple stages of aggregation process. Although the idea of secure data aggregation based on digital watermarking has been explored before, we aim to improve the efficiency of the scheme by examining several signature codes that could also decrease the watermark detection complexity. This is achieved by simultaneous embedding of several shifted watermark patterns into aggregated data stream, such that the contribution of each data-source is hidden in the relative shifts of the patterns. We, also, derive conditions to preserve the main statistical properties of data-streams prior to the embedding procedure. Therefore, we can guarantee that the embedding procedure does not compromise the usability of data streams for any operations that depends on these statistical characteristics. The simulation results show that the embedded watermarks can successfully be recovered with high confidence if proper hiding codes are chosen.
机译:在许多应用中,例如传感器网络,电子医疗保健和环境监控,数据会从多种资源中连续流式传输和合并,以便基于聚合的数据流做出决策。这些应用程序中的一个主要问题是确保聚合数据流的高度可信赖性,以进行正确的决策。例如,一个对手可能会损害一些数据源,并将虚假数据引入聚合的数据流中,并造成灾难性的后果。在这项工作中,我们提出了一种通过将几个签名代码嵌入数据流中(称为数字水印)来验证数据完整性的新颖方法。因此,即使数据经过聚合过程的多个阶段,也可以通过解码嵌入的签名来验证数据流的完整性。尽管之前已经探讨了基于数字水印的安全数据聚合的思想,但我们的目标是通过检查几个签名代码来提高该方案的效率,这些签名代码也可以降低水印检测的复杂性。这是通过将几个偏移的水印图案同时嵌入到聚合数据流中来实现的,这样每个数据源的贡献都隐藏在图案的相对偏移中。我们还推导了在嵌入过程之前保持数据流主要统计属性的条件。因此,我们可以保证嵌入过程不会损害依赖于这些统计特征的任何操作的数据流可用性。仿真结果表明,如果选择合适的隐藏码,则可以高信度成功地恢复嵌入的水印。

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