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.

Metadata

publication

Proceedings of the 15th Workshop on Cyber Security Experimentation and Test …, 2022

year

2022

publication date

2022/8/8

authors

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

link

https://dl.acm.org/doi/abs/10.1145/3546096.3546103

resource_link

https://dl.acm.org/doi/pdf/10.1145/3546096.3546103

book

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

pages

59-64