使用亲和传播聚类的物理层量化

Sujata Kadam, Joanne Gomes
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引用次数: 0

摘要

在当今世界,信息安全至关重要。传统上使用对称和非对称加密方法来保证信息的安全。但它们面临着高计算复杂度和密钥管理基础设施的问题。这些问题可以通过使用信道属性生成对称密钥的物理层密钥生成(PLKG)方案来解决。一个基本的PLKG系统包括探测无线信道,将探测到的样本量化并将其转换为比特,使用安全哈希函数在量化输出比特和隐私放大之间进行错误检测和校正。为了获得对称密钥,量化在PLKG中起着至关重要的作用。提出了基于亲和传播聚类(VQAPC)的矢量量化。当两个合法用户(Alice和Bob)将一组样本分配到不同的量化区域时,量化结果会存在差异,这种差异被称为分配不一致率(ADR)。利用MATLAB软件进行仿真。与现有的量化方法相比,所提出的量化方法- vqapc具有非常低的ADR。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Quantization at the Physical layer using Affinity Propagation Clustering
In today’s world security of information is of utmost importance. Traditionally symmetric and asymmetric cryptographic methods are used to keep information secure. But they face problems of high computational complexity and key management infrastructure. These issues can be resolved by Physical layer key generation (PLKG) schemes which use channel properties to generate a symmetric key. A basic PLKG system consists of probing the wireless channel, quantizing the probed samples and converting them into bits, error detection and correction between the quantized output bits and privacy amplification using secure hash functions. Quantization plays a critical role in PLKG in order to obtain the symmetric secret keys. This paper proposes Vector Quantization with Affinity Propagation Clustering (VQAPC). When the two legitimate users (Alice and Bob) assign a set of samples to different quantization regions, there will be difference in the quantization results which is called as Assignment Disagreement Rate(ADR). Simulation is done using MATLAB software. The proposed quantization method-VQAPC gives very low ADR as compared to the existing methods.
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