Abstract
The proposed dataset shows characteristics of simultaneous botnet attack activities. Botnet network traffic has sequentially interconnected as formed as bidirectional network flow (binetflow), which is combined with normal activities. The dataset is generated from a simulation process by extracting botnet pattern behaviors taken from CTU-13 and NCC datasets. The extraction results are utilized as the basis for simulations to produce a new dataset with simultaneous botnet attack activities. The term "simultaneous attack activities" refers to an attack activity that involves multiple botnets and happens at the same time. The dataset contains several botnet types distributed over three detection sensors. Each dataset has 18 network header features with a total recording duration of 8 h. The bot attack spreads must be appropriately handled by efficient processing, also known as parallel computation detection.