基于安全压缩感知的大数据隐私保护

王平; 张玉书; 何兴; 仲盛

doi:10.11959/j.issn.2096-0271.2020002

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基于安全压缩感知的大数据隐私保护

专题：大数据隐私保护 | 更新时间：2024-06-03

- 基于安全压缩感知的大数据隐私保护
- Big data privacy protection based on secure compressive sensing
- 大数据 2020年6卷第1期页码：2020002-1
- 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：
  
  [ "王平（1993- ），男，西南大学电子信息工程学院硕士生，主要研究方向为多媒体安全" ]
  [ "张玉书（1987- ），男，博士，南京航空航天大学计算机科学与技术学院教授，主要研究方向为多媒体安全、物联网与云计算安全" ]
  [ "何兴（1986- ），男，博士，西南大学电子信息工程学院教授，主要研究方向为计算智能" ]
  [ "仲盛（1974- ），男，博士，南京大学计算机科学与技术系教授，主要研究方向为密码学、博弈论及其在计算机网络、分布式系统中的应用" ]
- 基金信息：
  
  国家重点研发计划基金资助项目;The National Key Research and Development Program of China(2017YFB0802300);广西可信软件重点实验室研究课题基金资助项目;Guangxi Trusted Software Key Laboratory Research Project(kx201904)
- DOI：10.11959/j.issn.2096-0271.2020002
  中图分类号： TP309
- 网络首发：2020-01，
  
  纸质出版：2020-01-15
- 稿件说明：
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王平, 张玉书, 何兴, 等. 基于安全压缩感知的大数据隐私保护[J]. 大数据, 2020,6(1):2020002-1.

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.
王平, 张玉书, 何兴, 等. 基于安全压缩感知的大数据隐私保护[J]. 大数据, 2020,6(1):2020002-1. DOI： 10.11959/j.issn.2096-0271.2020002.

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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