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

该项目是加州州立大学波莫纳分校大数据安全和隐私本科生研究体验 (REU) 网站的更新。该 REU 站点将接待一群多元化的本科生，他们将在夏季花费 10 周的时间研究大数据和安全/隐私交叉领域的研究问题。 该 REU 网站探讨网络安全和大数据情报的相互作用，重点关注两个研究方面：(a) 大数据、模型和平台的安全和隐私，以及 (b) 大数据情报安全。学生将获得基本的大数据安全和隐私概念，并学习使用测试平台和工具。由教师顾问组成的跨学科小组将指导学生的研究项目，例如隐私保护深度学习、针对深度网络分类模型的 3D 对抗性攻击，以及使用自然语言处理根据个性偏见对网络钓鱼电子邮件内容进行分类。除了研究活动外，还为学生精心策划了各种职业生涯发展活动，包括在多个研讨会和研讨会上展示他们的研究成果，在特邀演讲者系列中与高级研究人员和同行互动以及对研究实验室进行实地考察。该网站计划吸引来自全国各地的优秀本科生，特别注重招收西班牙裔和女性学生，这些群体传统上在计算机领域代表性不足。该项目是加州理工波莫纳 (CPP) 大数据安全和隐私 REU 网站的更新，并将于 2021 年至 2024 年间与 CPP 教师导师一起提供每年为期 10 周的沉浸式本科生研究体验。该网站每年夏天将接待 10 名 REU 学生，其中 5 名来自加州理工学院波莫纳和其他机构的 5 名。学生将获得基本的数据安全和隐私概念，并在短期课程/实验室练习中学习使用测试平台和工具。教师顾问将指导学生在大数据和安全/隐私交叉领域的研究项目，重点关注两个方面：(a) 大数据、模型和平台的安全和隐私，以及 (b) 大数据安全智能。学生的研究主题包括基于全同态加密（FHE）的隐私保护深度学习、针对深度网络分类模型的3D对抗攻击、异构计算环境下大规模网络异常检测的并行算法以及使用自然语言处理根据个性偏见对网络钓鱼电子邮件内容进行分类等。除了研究活动外，学生还将参加各种专业职业发展活动，包括在多个研讨会和研讨会上展示他们的研究成果，并与高级研究人员和高级研究人员互动。与同行一起参加特邀演讲者系列以及对研究实验室进行实地考察。除了夏季之外，该 REU 网站还为学生提供持续支持，以实现他们在大数据和网络安全方面的职业目标，例如扩展他们的研究、完成论文提交以及准备研究生院申请。该奖项反映了 NSF 的法定使命，并通过使用基金会的智力价值和更广泛的影响审查标准进行评估，被认为值得支持。

This project is a renewal of the Research Experiences for Undergraduates (REU) Site in Big Data Security and Privacy at Cal Poly Pomona. This REU Site will host a diverse group of undergraduate students who will spend 10 weeks in summer working on the research problems in the intersection of big data and security/privacy. This REU site explores the interplay of cybersecurity and big data intelligence and focuses on two research aspects: (a) Security and Privacy of Big Data, Model and Platform and (b) Big Data Intelligence for Security. The students will acquire fundamental big data security and privacy concepts and learn to use testbeds and tools. An interdisciplinary group of faculty advisors will direct students’ research projects, for example, in privacy preserving deep learning, 3D adversarial attacks against deep network classification models, and the classification of phishing e-mail contents according to personality bias using natural language processing. In addition to research activities, various professional career development activities are well planned for students including, presenting their research at multiple symposia and seminars and interacting with senior researchers and peers in an Invited Speaker Series and on a field trip to research labs. 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.This project is a renewal of the REU Site in Big Data Security and Privacy at Cal Poly Pomona (CPP) and will offer an annual and immersive 10-week undergraduate research experience with CPP faculty mentors from 2021 to 2024. The site will host 10 REU students each summer, 5 from Cal Poly Pomona and 5 from other institutions. The students will acquire fundamental data security and privacy concepts and learn to use testbed and tools in the short course/lab exercises. Faculty advisors will direct students’ research projects in the intersection of big data and security/privacy with an emphasis on two aspects: (a) Security and Privacy of Big Data, Model and Platform and (b) Big Data Intelligence for Security. Student research topics include Fully Homomorphic Encryption (FHE) based privacy preserving deep learning, 3D adversarial attacks against deep network classification models, parallel algorithms for Large Scale Cyber Anomaly Detection on Heterogenous Computing Environments, and the classification of phishing e-mail contents according to personality bias using natural language processing, etc. In addition to research activities, students will participate in a variety of professional career development activities including, presenting their research at multiple symposia and seminars and interacting with senior researchers and peers in an Invited Speaker Series and on a field trip to research labs. Beyond summer, this REU site also provides students with continuous support towards their career goals in big data and cybersecurity, e.g., extending their research, completing paper submission, and preparing for graduate school applications.This award reflects NSF's statutory mission and has been deemed worthy of support through evaluation using the Foundation's intellectual merit and broader impacts review criteria.