REU Site: Undergraduate Research Experiences in Big Data Security and Privacy

REU 网站：大数据安全和隐私方面的本科生研究经验

• 批准号: 1758017
• 负责人: Tingting Chen
• 金额: $ 28万
• 依托单位: Cal Poly Pomona Foundation, Inc.
• 依托单位国家: 美国
• 项目类别: Standard Grant
• 财政年份: 2018
• 资助国家: 美国
• 起止时间: 2018-02-01 至 2021-01-31
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=1758017&HistoricalAwards=false
• 关键词: REU; Site; Undergraduate; Research; Experiences

This funding establishes a new Research Experiences for Undergraduates (REU) Site at California State Polytechnic University, Pomona. This REU Site will host a diverse group of undergraduate students who will spend their summer working on cutting-edge big data security research problems in genomic data privacy, secure multiparty cloud computation, and hybrid data center security. This REU Site provides students with the opportunities to explore the challenges of big data security and privacy using state-of-the art tools and testbeds. Security and privacy issues are magnified by big data, with the diversity of data sources and formats as well as large-scale cloud infrastructures needed to support big data applications. As a result, traditional security mechanisms are not adequate and new mechanisms and policies related to the security and privacy of big data are needed. The research is led by an interdisciplinary group faculty actively engaged in cybersecurity research. The site will provide mentoring and other professional development opportunities that should impact the future academic and professional careers of the students. The site plans to attract talented undergraduate students from across the nation, particularly focusing on recruiting Hispanic and women students, groups traditionally under-represented in the computing fields.The research projects in this REU Site address new big data security and privacy problems, such as genomic data privacy protection, accelerated encryption algorithms for genomic data in acquisition, privacy preserving big data mining, secure multiparty computation on clouds, security compliance measurement in hybrid data centers, and data governance in migration among clouds. While these topics can be closely interconnected, they address security and privacy issues in different phases of the big data life cycle. The projects will use a new High Performance Computing Cluster and a student run campus data center to provide research that in both theory and application in an emerging area of research.

这笔资金在波莫纳的加州州立理工大学建立了一个新的本科生研究体验(REU)网站。这个REU网站将接待一群不同的本科生，他们将在夏天研究基因组数据隐私、安全多方云计算和混合数据中心安全方面的尖端大数据安全研究问题。该REU网站为学生提供了使用最先进的工具和试验台探索大数据安全和隐私挑战的机会。大数据放大了安全和隐私问题，数据来源和格式的多样性以及支持大数据应用所需的大规模云基础设施。因此，传统的安全机制并不充分，需要与大数据安全和隐私相关的新机制和政策。这项研究是由一个积极从事网络安全研究的跨学科组织教员领导的。该网站将提供指导和其他职业发展机会，这些机会应该会对学生未来的学术和职业生涯产生影响。该网站计划吸引来自全国各地的有才华的本科生，特别是招收西班牙裔和女性学生，这些学生在计算领域传统上代表不足。该REU网站的研究项目解决了新的大数据安全和隐私问题，如基因组数据隐私保护、获取基因组数据的加速加密算法、隐私保护大数据挖掘、云上安全多方计算、混合数据中心的安全合规性衡量，以及云之间迁移的数据治理。虽然这些主题可以紧密联系在一起，但它们解决了大数据生命周期不同阶段的安全和隐私问题。这些项目将使用一个新的高性能计算集群和一个学生管理的校园数据中心，以提供在一个新兴研究领域的理论和应用研究。

项目成果

Towards Better Accuracy and Robustness with Localized Adversarial Training

• DOI: 10.1609/aaai.v33i01.330110017
• 发表时间: 2019-07
• 作者: Eitan Rothberg;Tingting Chen;Hao Ji

An Authentication System using Neurological Responses to Music

使用音乐神经反应的身份验证系统

• DOI: 10.1109/bigdata47090.2019.9006491
• 发表时间: 2019
• 期刊: 2019 IEEE International Conference on Big Data (Big Data
• 作者: Cauthen, Joseph M;Gandre, Tejas;Espinoza, Marco A.;Patel, Meetkumar J;Husain, Mohammad I
• 通讯作者: Husain, Mohammad I

Privacy Preserving Fisher’s Exact Test on Genomic Data

隐私保护费舍尔对基因组数据的精确检验

• DOI: 10.1109/bigdata.2018.8622575
• 发表时间: 2018
• 期刊: 2018 IEEE International Conference on Big Data (Big Data
• 作者: Poon, Anna;Jankly, Steve;Chen, Tingting
• 通讯作者: Chen, Tingting

Privacy Preserving Inference with Convolutional Neural Network Ensemble

• DOI: 10.1109/ipccc50635.2020.9391544
• 发表时间: 2020-11
• 期刊: 2020 IEEE 39th International Performance Computing and Communications Conference (IPCCC)
• 作者: Alexander Xiong;M. Nguyen;Andrew So;Tingting Chen

On Multiview Robustness of 3D Adversarial Attacks

• DOI: 10.1145/3311790.3396652
• 发表时间: 2020-07
• 期刊: Practice and Experience in Advanced Research Computing
• 作者: Philip Yao;Andrew So;Tingting Chen;Hao Ji