High Bandwidth Biometrics Data Hosting and Analytics in Cloud-based Storage Systems

Cloud hosting environments include large scale distributed storage systems. With the advent of Big Data, especially newer biomedical and biometrics data, collected from wearable monitoring devices, there is a high need for Cloud-based solutions for large scale storage and high bandwidth on-the-fly data analysis for such data. A key problem for IT companies that collect large amounts of biometrics data on-the-fly is their need for real-time solutions for anomaly detection in the collected data. This work focuses on (a) on-the-fly biometric data analysis and anomaly detection and (b) on-the-fly analysis of computer system data for anomaly detection of system behavior. The proposed solution will minimize the data analysis search space of the stored data. We will evaluate our solutions in collaboration with the partner organization for types of human and system biometrics data on various distributed storage systems.

Faculty Supervisor:

Cristiana Amza

Student:

Stelios Sotiriadis

Partner:

Avertus Epilepsy Technologies Inc.

Discipline:

Engineering - computer / electrical

Sector:

Information and communications technologies

University:

University of Toronto