Advanced Security and Privacy Technologies for Data Protection: Analysis, Design and Application in Big Data Era
先进的数据保护安全与隐私技术:大数据时代的分析、设计与应用
基本信息
- 批准号:RGPIN-2017-04009
- 负责人:
- 金额:$ 1.46万
- 依托单位:
- 依托单位国家:加拿大
- 项目类别:Discovery Grants Program - Individual
- 财政年份:2020
- 资助国家:加拿大
- 起止时间:2020-01-01 至 2021-12-31
- 项目状态:已结题
- 来源:
- 关键词:
项目摘要
Big data has been widely regarded as a new “natural resource” and has become a key driver of economic growth and competitiveness in Canada. In order to adapt Canada to the big data era, we need to prepare not only a new generation of data engineers skilled at managing big data, but also reliable big data process platforms to enable secure and privacy-preserving collaborative computing in big data era. The broad objective of the proposed research is therefore to focus on efficient, secure, and privacy-preserving big data processing and collaborative computing.
As big data is characterized by high volume, velocity, and variety (“3V”), traditional security and privacy solutions cannot be directly migrated to fully address newly-emerging challenges in the context of big data. Therefore, we need to pay significant attention to big data security and privacy research. However, there are currently few works dedicated to security and privacy challenges in big data. To fill this gap, the efforts in this proposal shall shed new light on big data security and privacy research. Specifically, the proposed research will investigate a set of advanced security and privacy technologies using an interdisciplinary approach, i.e., by combining cryptography, distributed computing, and data mining techniques, to provide secure and reliable data collection, storage, transmission, and processing for big data. In particular, this proposal will address significant technical challenges arising from “3V” characteristics of big data, in the following four thrusts:
i) developing lightweight and secure cryptographic protocols for big data in the phase of big data acquisition, organization, and analysis;
ii) developing secure distributed programming frameworks for computing in big data;
iii) developing privacy-preserving big data mining to prevent inadvertent privacy disclosures in big data; and
iv) developing reliable, provenance-integrated, and access-controllable data provenance for big data.
The proposed research will draw intensively and extensively on the Principal Investigator's research expertise, as well as strong supports from the CIC (Canadian Institute for Cybersecurity) affiliated with the University of New Brunswick Faculty of Computer Science. This cutting-edge research will generate new ideas and knowledge for the evolution of secure big data, enable HQP training and provide new secure big data solutions for Canada. The HQP trained through the program will be equipped with big data and security technologies, as well as wireless communications and mobile computing; these are crucial for success in the era of the Internet of Things and big data computing, and will help to ensure a prosperous future for the Canadian IT industry.
大数据被广泛认为是一种新的“自然资源”,已成为加拿大经济增长和竞争力的关键驱动力。为了使加拿大适应大数据时代,我们不仅需要培养擅长管理大数据的新一代数据工程师,还需要培养可靠的大数据处理平台,使大数据时代能够实现安全和隐私保护的协同计算。因此,拟议研究的广泛目标是专注于高效、安全和隐私保护的大数据处理和协作计算。
由于大数据具有大容量、大速度、大多样性(3V)的特点,传统的安全和隐私解决方案无法直接迁移,以全面应对大数据背景下的新挑战。因此,我们需要高度重视大数据安全和隐私研究。然而,目前专门研究大数据中的安全和隐私挑战的作品很少。为了填补这一空白,该提案中的努力将为大数据安全和隐私研究带来新的曙光。具体地说,拟议的研究将使用跨学科方法调查一套先进的安全和隐私技术,即结合密码学、分布式计算和数据挖掘技术,为大数据提供安全可靠的数据收集、存储、传输和处理。特别是,这项提案将在以下四个方面解决大数据“3V”特性带来的重大技术挑战:
I)在大数据采集、组织、分析阶段开发轻量级、安全的大数据加密协议;
二)为大数据计算开发安全的分布式编程框架;
Iii)开发保护隐私的大数据挖掘,以防止大数据中无意中泄露隐私;以及
四)为大数据开发可靠、来源集成和访问可控的数据来源。
拟议的研究将深入和广泛地利用首席调查员的研究专长,以及新布伦瑞克大学计算机科学学院附属的加拿大网络安全研究所(CIC)的大力支持。这一前沿研究将为安全大数据的演进产生新的想法和知识,启用HQP培训,并为加拿大提供新的安全大数据解决方案。通过该计划培养的HQP将配备大数据和安全技术,以及无线通信和移动计算;这些对物联网和大数据计算时代的成功至关重要,并将有助于确保加拿大IT行业的繁荣未来。
项目成果
期刊论文数量(0)
专著数量(0)
科研奖励数量(0)
会议论文数量(0)
专利数量(0)
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Lu, Rongxing其他文献
A Secure Handshake Scheme with Symptoms-Matching for mHealthcare Social Network
- DOI:
10.1007/s11036-010-0274-2 - 发表时间:
2011-12-01 - 期刊:
- 影响因子:3.8
- 作者:
Lu, Rongxing;Lin, Xiaodong;Shen, Xuemin - 通讯作者:
Shen, Xuemin
An Efficient Merkle-Tree-Based Authentication Scheme for Smart Grid
一种基于默克尔树的智能电网高效认证方案
- DOI:
10.1109/jsyst.2013.2271537 - 发表时间:
2014-06-01 - 期刊:
- 影响因子:4.4
- 作者:
Li, Hongwei;Lu, Rongxing;Shen, Xuemin (Sherman) - 通讯作者:
Shen, Xuemin (Sherman)
New (t,n) threshold directed signature scheme with provable security
- DOI:
10.1016/j.ins.2007.07.025 - 发表时间:
2008-02-01 - 期刊:
- 影响因子:8.1
- 作者:
Lu, Rongxing;Lin, Xiaodong;Liang, Xiaohui - 通讯作者:
Liang, Xiaohui
5G Vehicle-to-Everything Services: Gearing Up for Security and Privacy
- DOI:
10.1109/jproc.2019.2948302 - 发表时间:
2020-02-01 - 期刊:
- 影响因子:20.6
- 作者:
Lu, Rongxing;Zhang, Lan;Fang, Yuguang - 通讯作者:
Fang, Yuguang
Achieve Privacy-Preserving Priority Classification on Patient Health Data in Remote eHealthcare System
- DOI:
10.1109/access.2019.2891775 - 发表时间:
2019-01-01 - 期刊:
- 影响因子:3.9
- 作者:
Wang, Guoming;Lu, Rongxing;Guan, Yong Liang - 通讯作者:
Guan, Yong Liang
Lu, Rongxing的其他文献
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{{ truncateString('Lu, Rongxing', 18)}}的其他基金
Advanced Security and Privacy Techniques for Secure Big Data Query, Sharing and Processing
用于安全大数据查询、共享和处理的先进安全和隐私技术
- 批准号:
RGPIN-2022-03244 - 财政年份:2022
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced Security and Privacy Technologies for Data Protection: Analysis, Design and Application in Big Data Era
先进的数据保护安全与隐私技术:大数据时代的分析、设计与应用
- 批准号:
RGPIN-2017-04009 - 财政年份:2021
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced Security and Privacy Technologies for Data Protection: Analysis, Design and Application in Big Data Era
先进的数据保护安全与隐私技术:大数据时代的分析、设计与应用
- 批准号:
RGPIN-2017-04009 - 财政年份:2019
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced Security and Privacy Technologies for Data Protection: Analysis, Design and Application in Big Data Era
先进的数据保护安全与隐私技术:大数据时代的分析、设计与应用
- 批准号:
RGPIN-2017-04009 - 财政年份:2018
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
Advanced Security and Privacy Technologies for Data Protection: Analysis, Design and Application in Big Data Era
先进的数据保护安全与隐私技术:大数据时代的分析、设计与应用
- 批准号:
RGPIN-2017-04009 - 财政年份:2017
- 资助金额:
$ 1.46万 - 项目类别:
Discovery Grants Program - Individual
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