Abstract

Researchers are in constant need of reliable data to develop and evaluate AI/ML methods for networks and cybersecurity. While Internet measurements can provide realistic data, such datasets lack ground truth about application flows. We present a ∼ 750GB dataset that includes ∼ 2000 systematically conducted experiments and the resulting packet captures with video streaming, video teleconferencing, and cloud-based document editing applications. This curated and labeled dataset has bidirectional and encrypted traffic with complete ground truth that can be widely used for assessments and evaluation of AI/ML algorithms.

Date

2022

Authors

Calvin Ardi, Connor Aubry, Brian Kocoloski, Dave DeAngelis, Alefiya Hussain, Matt Troglia, Stephen Schwab

Book

Proceedings of the 15th Workshop on Cyber Security Experimentation and Test

Pages

59-64