ACS MILCOM 2016 Datasets

The datasets generated for the Applied Communication Sciences' MILCOM 2016 paper “Four Labeled Datasets to Enable Reproducible Cyber Research” are available using the links below.

Please cite the following paper when referencing these datasets:
T. Bowen, A. Poylisher, C. Serban, R. Chadha, C. J. Chiang, L. Marvel. “Enabling Reproducible Cyber Research – Four Labeled Datasets”. IEEE MILCOM 2016.

File Name	Size	Description	MD5
Datasets_A-E_Descriptions.pdf	2M	Full Dataset description document	acdaff8babef45780e486401b08f4cf0
dataSetAv1.7z	842M	ACS pseudo botnet - download	8729b9ad158a749af496dd0f408e672f
dataSetAv2.7z	33G	ACS pseudo botnet - download	ad7730b833c9e98968a515d320844d7d
dataSetBv1.7z	7G	ACS pseudo botnet - download	82cc959c61a0a5190618d51d957ffdd7
dataSetBv2.7z	34G	ACS pseudo botnet - download	5c2faafcb45d2e01941f92987cca1d5a
dataSetCv1.7z	13G	ACS pseudo botnet - website	af2a2c7b5afef45161f853ad9ed7791a
dataSetCv2.7z	71G	ACS pseudo botnet - website	12dc1aecec9749389c223f14cb52771c
dataSetDLamp.7z	22G	ACS pseudo botnet - LAMP variant	433a896826279863b881282b69c064d3
dataSetDNJS.7z	41G	ACS pseudo botnet - Node.js variant	02ee78a80b67b50931713e87298710f5
dataSetEAggregator.7z	44G	Aggregator Attack	5ca643a1adfbd481173017a01bc381dc
dataSetEBatteryDrain.7z	10G	Battery Drain Attack	87f54dae6e99d74aa9727b03064abee6
dataSetESlowloris.7z	42G	Slow Loris Attack	794abd20332f20dc325b6c354d8f2d2f
dataSetESynFlood.7z	29G	Syn Flood Attack	5f212841d6bc6948b2b04c68f5699b6b
deliveredLabels.7z	74M	Data Set Labels	c1c2c60a9d84bbef932d983148775421
utilities.7z	6174	Dataset Utilities	38a008a0c42928bdad52bd3eba34355e

The ACS MILCOM 2016 dataset was originally linked from here:
https://cybervan.appcomsci.com:9000/datasets