The datasets generated for the Applied Communication Sciences' MILCOM 2016 paper โFour Labeled Datasets to Enable Reproducible Cyber Researchโ 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. โEnabling Reproducible Cyber Research โ Four Labeled Datasetsโ. IEEE MILCOM 2016.
File Name | Size | Description | MD5 |
---|---|---|---|
Datasets_A-E_Descriptions.pdf | ย ย 2M | Full Dataset description document | acdaff8babef45780e486401b08f4cf0 |
dataSetAv1.7z | 842M | ACS pseudo botnet - download | 8729b9ad158a749af496dd0f408e672f |
dataSetAv2.7z | ย 33G | ACS pseudo botnet - download | ad7730b833c9e98968a515d320844d7d |
dataSetBv1.7z | ย ย 7G | ACS pseudo botnet - download | 82cc959c61a0a5190618d51d957ffdd7 |
dataSetBv2.7z | ย 34G | ACS pseudo botnet - download | 5c2faafcb45d2e01941f92987cca1d5a |
dataSetCv1.7z | ย 13G | ACS pseudo botnet - website | af2a2c7b5afef45161f853ad9ed7791a |
dataSetCv2.7z | ย 71G | ACS pseudo botnet - website | 12dc1aecec9749389c223f14cb52771c |
dataSetDLamp.7z | ย 22G | ACS pseudo botnet - LAMP variant | 433a896826279863b881282b69c064d3 |
dataSetDNJS.7z | ย 41G | ACS pseudo botnet - Node.js variant | 02ee78a80b67b50931713e87298710f5 |
dataSetEAggregator.7z | ย 44G | Aggregator Attack | 5ca643a1adfbd481173017a01bc381dc |
dataSetEBatteryDrain.7z | ย 10G | Battery Drain Attack | 87f54dae6e99d74aa9727b03064abee6 |
dataSetESlowloris.7z | ย 42G | Slow Loris Attack | 794abd20332f20dc325b6c354d8f2d2f |
dataSetESynFlood.7z | ย 29G | Syn Flood Attack | 5f212841d6bc6948b2b04c68f5699b6b |
deliveredLabels.7z | ย 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