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, to appear.

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

MILCOM 2016 Logo

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