@inproceedings{10.1145/3546096.3546103,
author = {Ardi, Calvin and Aubry, Connor and Kocoloski, Brian and DeAngelis, Dave and Hussain, Alefiya and Troglia, Matt and Schwab, Stephen},
title = {The DARPA SEARCHLIGHT Dataset of Application Network Traffic},
year = {2022},
isbn = {9781450396844},
publisher = {Association for Computing Machinery},
address = {New York, NY, USA},
url = {https://doi.org/10.1145/3546096.3546103},
doi = {10.1145/3546096.3546103},
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.},
booktitle = {Proceedings of the 15th Workshop on Cyber Security Experimentation and Test},
pages = {59–64},
numpages = {6},
keywords = {network traffic, network experimentation, datasets},
location = {Virtual, CA, USA},
series = {CSET '22}
}

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