Dear all, 

We have submitted the paper „LITNET-2020: an annotated real-world network flow dataset for network intrusion detection“ to the journal Electronics (ISSN 2079-9292)

Abstract: Network intrusion detection is one of the main problems in ensuring security of modern computer networks, wireless sensor networks (WSN) and Internet-of-Things (IoT). Do develop efficient network intrusion detection methods, the realistic and up-to-date network flow datasets are required. Despite several recent efforts, there is still the lack of real-world network-based datasets which can capture modern network traffic cases and provide examples of many different types of network intrusions. To alleviate this need, we present LITNET-2020, a new annotated network benchmark dataset obtained from the real-world academic network. The dataset presents real-world examples of normal and under-attack network traffic. We describe and analyze 85 network flow features of the dataset and 12 attack types. The presented dataset is made freely available for research purposes.

This paper is still under evaluation. 

If it gets accepted, we will acknowledge SPARTA.

Best,

Algimantas Venčkauskas

Kauno technologijos universitetas