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

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经验（REU）网站。 这个REU网站将主办一个多样化的本科生群体，他们将在夏天致力于基因组数据隐私，安全多方云计算和混合数据中心安全性方面的尖端大数据安全研究问题。 这个REU网站为学生提供了使用最先进的工具和测试平台探索大数据安全和隐私挑战的机会。安全和隐私问题被大数据放大，数据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，传统的安全机制是不够的，需要与大数据的安全和隐私相关的新机制和政策。该研究由积极从事网络安全研究的跨学科小组教师领导。该网站将提供指导和其他专业发展机会，应该影响学生未来的学术和职业生涯。该网站计划吸引来自全国各地的有才华的本科生，特别注重招收西班牙裔和女性学生，这些群体在计算领域传统上代表性不足。该REU网站的研究项目解决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，云上的安全多方计算、混合数据中心中的安全合规性测量以及云间迁移中的数据治理。 虽然这些主题可以密切相关，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。该项目将使用一个新的高性能计算集群和一个学生运行的校园数据中心，以提供研究，在理论和应用在一个新兴的研究领域。

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.