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: 2050826
• 负责人: Tingting Chen
• 金额: $ 40.49万
• 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: 2021
• 资助国家: 美国
• 起止时间: 2021-03-01 至 2024-02-29
• 项目状态: 已结题
• 来源: https://www.nsf.gov/awardsearch/showAward?AWD_ID=2050826&HistoricalAwards=false
• 关键词: REU; Site; Undergraduate; Research; Experiences

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.

该项目是Cal Poly Pomona大数据安全和隐私本科生研究经验（REU）网站的更新。这个REU网站将主办一个多样化的本科生群体，他们将在夏季花10周时间研究大数据和安全/隐私交叉点的研究问题。 该网站探讨了网络安全和大数据智能的相互作用，并侧重于两个研究方面：（a）大数据，模型和平台的安全和隐私以及（B）安全的大数据智能。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。一个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钓鱼电子邮件内容进行分类。除了研究活动，各种专业的职业发展活动都为学生精心策划，包括在多个研讨会和研讨会上展示他们的研究，并与资深研究人员和同行在特邀演讲者系列和实地考察研究实验室互动。该网站计划吸引来自全国各地的优秀本科生，特别是侧重于招募西班牙裔和女性学生，该项目是加州理工大学波莫纳分校（CPP）大数据安全和隐私REU网站的更新，并将提供年度和身临其境的10-周本科研究经验与CPP教师导师从2021年至2024年。该网站每年夏天将接待10名REU学生，5名来自加州理工大学波莫纳分校，5名来自其他机构。学生将获得基本的数据安全和隐私概念，并学习在短期课程/实验室练习中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/隐私的交叉点的研究项目，重点放在两个方面：（a）大数据，模型和平台的安全和隐私以及（B）安全的大数据智能。学生的研究课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钓鱼电子邮件内容进行分类等。学生将参加各种职业发展活动，包括在多个研讨会和研讨会上展示他们的研究，并与资深研究人员和同行在特邀演讲者系列和实地考察研究实验室进行互动。除了夏天，这个REU网站还为学生提供持续的支持，以实现他们在大数据和网络安全方面的职业目标，例如，该奖项反映了NSF的法定使命，并通过使用基金会的知识价值和更广泛的影响审查标准进行评估，被认为值得支持。

项目成果

Formulating Parallel Supervised Machine Learning Designs For Anomaly-Based Network Intrusion Detection in Resource Constrained Use Cases

• DOI: 10.1109/mass56207.2022.00117
• 发表时间: 2022-10
• 期刊: 2022 IEEE 19th International Conference on Mobile Ad Hoc and Smart Systems (MASS)
• 作者: Varun Joshi;John Korah

Mobility Scooter User Driving Behavior Classification based on Deep Neural Networks

基于深度神经网络的代步车用户驾驶行为分类

• DOI: 10.1109/bigdata55660.2022.10020335
• 发表时间: 2022
• 期刊: 2022 IEEE International Conference on Big Data (Big Data
• 作者: Cruz, Marc;De Beleh, Sherelene;Janairo, Russel;Zhao, Yanbo;Raheja, Isha;Chen, Tingting
• 通讯作者: Chen, Tingting