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.
