NSF Research Experiences for Undergraduates (REU) Cybersecurity

Deep Learning Driven Cybersecurity Research in a Multidisciplinary Environment

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Cybersecurity is a priority area of national need. As a multidisciplinary field, cybersecurity requires that the professionals have knowledge and skills in various disciplines. The REU site program offers unique multidisciplinary learning and research opportunities for undergraduate students in an inherently multidisciplinary cybersecurity discipline. Each student will be able to select his/her preferred mentor and work with the mentor to select an REU research project based on his/her interests and background. The students will master research methodologies and obtain valuable research experiences in an area of critical national need, and also better prepare for graduate studies. The REU program is also enriched through various seminars, social activities, and field trips to Naval Base Norfolk, and Navy Cyber Defense Operation Command (NCDOC).

Apply by March 1, 2022

About

Support for Research Activities

$7,200 for stipends and food
Free on-campus housing for 10 weeks and travel support

(Conditioned on that the REU program is hosted on-site at
ODU)

Qualifications

U.S. citizen or permanent resident
Must be an undergraduate student during the program period

(Graduation date after the program period)
Preferred GPA 3.0+
Students from all disciplines or majors will be considered

Requirements

Perform at least 30 hours/week research with the mentor for 10 weeks

(Starting from May 31, 2022)
Attend weekly research meeting and other events
Write a research report and create a poster at the end of the program

Past Projects

The REU project is selected together by the student and the mentor based on the student interests and background. The following is a list of selected past REU projects.

Measurement of Energy Impact on Blockchain Technologies: Cryptocurrency Mining
Visualization and Prevention of Backdoor Attacks in CNN model
Person Identification from Skeleton Data via a Convolutional Co-occurrence Feature Learning Network
Using Torchattacks to Improve the Robustness of Models with Adversarial Training
The Effect of the Coronavirus on Cyberbullying Research Methods

View More

Deep Learning Based Malware Classification Using Variational Autoencoders (VAE)
Cybersecurity and Cybercrime: a Multi-Level Analysis
Application of Homomorphic Encryption on Mesh Smoothing
Generalized Deep Learning Model for Automated Threat Detection
AccPhantom: An Accelerometer Side-Channel Attack Approach Utilizing Connectionist Temporal Classification on Recurrent Neural Networks
Continuous Authentication of Smartphone users: Touchscreen interactions
Despect: A Framework for the Creation of Microarchitectural Datasets
Data Augmentation with Generative Models for Improved Malware Detection: A Comparative Study
Radio Frequency Toolbox for Detection and Classification of Drones
Deep Learning Malware Detection using End-to-end Training
An Insider Look at Your Insider Threat: An Analysis of Insider Breaches
Twitter Social Bots: DIY Grassroots Campaign
Improve Security in Smart Drones
Transfer Learning for CNN based Robust Face Recognition in NAO Humanoid Robot
Comparing Security Risks to PayPal Transactions in the United States and Mexico
Inferring Web Browsing Usage Over Encrypted Data Traffic
Intrusion Detection using Machine Learning
Cybercriminals and the Punishment
Malicious Skill Design for Privacy Intrusion against Amazon Alexa Devices
Cyber Hygiene Knowledge and Behaviors of End Users