Preserving Privacy at Edge Devices

The aim of this project is to develop an application that can proactively protect users from identity theft and create awareness around safe digital practices. For this, we will be developing novel ways of extracting utility out of data and helping users to maintain a least-risk profile score. Most of the computations will be done on edge devices and computations will be prioritized based on value extractions. This research will help to bridge the gap between the accuracy and efficiency of the models to preserve privacy. Testing the models in real case scenarios will give us the pathway to have a mass reach and usability.

Faculty Supervisor:

Dhirendra Shukla

Student:

Partner:

Springboard Atlantic Inc.

Discipline:

Computer science

Sector:

Cyber Security; Artificial Intelligence; Technology

University:

University of New Brunswick

Program: