Big data privacy protection based on secure compressive sensing

Ping WANG; Yushu ZHANG; Xing HE; Sheng ZHONG

doi:10.11959/j.issn.2096-0271.2020002

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Big data privacy protection based on secure compressive sensing

TOPIC：PRIVACY PROTECTION OF BIG DATA | 更新时间：2024-06-03

- Big data privacy protection based on secure compressive sensing
- Big Data Research Vol. 6, Issue 1, Pages: 2020002-1(2020)
- 作者机构：
  
  1. 西南大学电子信息工程学院，重庆 400715
  2. 南京航空航天大学计算机科学与技术学院，江苏南京 211106
  3. 南京大学计算机科学与技术系，江苏南京 210023
- 作者简介：
- 基金信息：
- DOI：10.11959/j.issn.2096-0271.2020002
  CLC： TP309
- Online First：2020-01，
  
  Published：15 January 2020
- 稿件说明：
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Ping WANG, Yushu ZHANG, Xing HE, et al. Big data privacy protection based on secure compressive sensing[J]. Big Data Research, 2020, 6(1): 2020002-1.
DOI：

Ping WANG, Yushu ZHANG, Xing HE, et al. Big data privacy protection based on secure compressive sensing[J]. Big Data Research, 2020, 6(1): 2020002-1. DOI： 10.11959/j.issn.2096-0271.2020002.

摘要

当前的数据“大爆炸”主要受万物互联的驱动，服务于人类衣食住行的各类物联网感知设备时刻在捕获个人隐私数据，然而，这些隐私数据已成为网络攻击的重点目标。分析了资源受限的物联网应用中的数据安全问题，介绍了基于压缩感知理论的隐私保护技术—— 安全压缩感知，提出了相应的大数据采集方案，并且通过安全性理论和实验分析给出了结论性的呼吁：将安全压缩感知作为一种感知层内置的轻量级加密机制，以近乎零的成本为数据提供第一层安全防护。

Abstract

The current “big bang” of data is mainly driven by interconnection of all things.Various types of IoT sensing devices serving in daily life are constantly capturing personal privacy data.However

these privacy data have become the key targets of network attacks.Data security issues in the resource-constrained IoT applications were analyzed

a novel privacy protection technique based on compressive sensing theory was introduced

which is called secure compressed sensing

and a corresponding big data collection scheme was proposed.As demonstrated by the theoretical and experimental security analysis

there is a conclusive appeal for that secure compressive sensing can be used as a lightweight encryption mechanism which is built into the perception layer to provide first-level security protection for data at almost zero cost.

关键词

Keywords

references

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