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Light-weight and secure aggregation protocols based on Bloom filters

机译:基于Bloom过滤器的轻量级安全聚合协议

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In this paper we present a light-weight data aggregation protocol based on probabilistic data structure used for representing a subset of elements called Bloom filter. Our construction is optimal (up to a small multiplicative constant) in terms of the size of the aggregated data representation. Moreover, all necessary operations have minimal computational and memory requirements (no asymmetric cryptography is used) and provides data confidentiality in a model with an adversary with moderate capabilities. This protocol is adequate for systems of very constrained devices (like sensors) and is based solely on Bloom filters. Finally, we present two modifications of the basic protocol that can provide immunity against substantially stronger models of adversaries for the price of slightly more complex computations and increased size of the transmitted data. The security results of our protocol are mainly based on analysis of some properties of Bloom filters. We first investigate how much information about the number of represented elements can be learned by an external observer given a Bloom filter (or a part of it). The information leakage is expressed in terms of (α,β)-indistinguishability notion. We believe that this algorithm is quite general and can be applied for security analysis of other communication protocols based on Bloom filters.
机译:在本文中,我们提出了一种基于概率数据结构的轻量级数据聚合协议,该协议用于表示称为布隆过滤器的元素子集。就聚合数据表示的大小而言,我们的构造是最佳的(最大乘积常数很小)。而且,所有必需的操作对计算和内存的要求都最低(不使用非对称加密),并且在具有中等能力的带有对手的模型中提供数据机密性。该协议适用于设备非常受限的系统(例如传感器),并且仅基于Bloom过滤器。最后,我们提出了对基本协议的两种修改,它们可以以稍微更复杂的计算和增加的传输数据大小为代价,提供针对实质上更强大的对手模型的免疫力。我们协议的安全性结果主要基于对Bloom过滤器某些属性的分析。我们首先研究给定Bloom过滤器(或其一部分)的外部观察者可以了解多少有关表示元素的数量的信息。信息泄漏用(α,β)不可区分性概念表示。我们认为该算法非常通用,可用于基于Bloom过滤器的其他通信协议的安全性分析。

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