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Hiding Secret Points Amidst Chaff

机译:隐藏在查夫之中的秘密要点

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摘要

Motivated by the representation of biometric and multimedia objects, we consider the problem of hiding noisy point-sets using a secure sketch. A point-set X consists of s points from a d-dimensional discrete domain [0, N — 1]~d. Under permissible noises, for every point < x_1,..,x_d > ∈ X, each x_i may be perturbed by a value of at most δ. In addition, at most t points in X may be replaced by other points in [0, N — 1]~d. Given an original X, we want to compute a secure sketch P. A known method constructs the sketch by adding a set of random points R, and the description of (X ∪ R) serves as part of the sketch. However, the dependencies among the random points are difficult to analyze, and there is no known non-trivial bound on the entropy loss. In this paper, we first give a general method to generate R and show that the entropy loss of (X ∪ R) is at most s(d log Δ + d + 0.443), where Δ = 2δ + 1. We next give improved schemes for d = 1, and special cases for d = 2. Such improvements are achieved by pre-rounding, and careful partition of the domains into cells. It is possible to make our sketch short, and avoid using randomness during construction. We also give a method in d = 1 to demonstrate that, using the size of R as the security measure would be misleading.
机译:受生物特征和多媒体对象表示的启发,我们考虑使用安全草图隐藏嘈杂点集的问题。点集X由d维离散域[0,N_1]〜d中的s个点组成。在允许的噪声下,对于每个∈X,每个x_i可能最多被δ值扰动。另外,X中的t个点最多可以被[0,N_1]〜d中的其他点替换。给定原始X,我们想计算一个安全草图P。一种已知方法通过添加一组随机点R来构造草图,并且(X∪R)的描述用作草图的一部分。但是,随机点之间的依赖性很难分析,并且熵损失没有已知的非平凡约束。在本文中,我们首先给出一种通用的生成R的方法,并证明(X∪R)的熵损失最大为s(d logΔ+ d + 0.443),其中Δ=2δ+ 1。 d = 1的方案和d = 2的特殊情况。这种改进是通过预先舍入并小心地将域划分到单元中来实现的。可以使草图更短,并避免在构造过程中使用随机性。我们还给出了d = 1中的一种方法,以证明使用R的大小作为安全性度量会产生误导。

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