Optimizing Cybersecurity Data Platform Operational Cost

We focus on building the systems that allow for the storage and analysis of big data for preventing cybersecurity attacks. This telemetry data is collected from customers by leveraging endpoint, network, and cloud data sources both inside and outside our customers’ networks. Our team then builds products that allows our customers as well as our own employees to make business intelligence queries against this large set of data, to better understand their security posture. As our customers grow, the services which host and serve data will need to scale as well. Arctic Wolf needs to make sure that the operational costs are optimized to ensure cost savings and scalability. This is a problem which needs to factor in the continuously changing landscape in technologies, the cost of upkeep to operate these technologies at scale, and continuously changing access patterns. The goal of this project is to research efficient use of cloud resources and services which is used to ingest, organize, and store billions of data points per day

Faculty Supervisor:

Shurui Zhou

Student:

Partner:

Arctic Wolf Networks

Discipline:

Computer science

Sector:

Information and cultural industries; Professional, scientific and technical services

University:

University of Toronto

Program: