This article describes how sequential data modeling is a relevant task in Cybersecurity.
Sequences are attributed temporal characteristics either explicitly or implicitly. Recurrent …

Network security field had gained research community attention in the last decade due to its
growing importance. This paper addresses directly one vital problem in that field is “Intrusion …

The evolution of communication and information systems has raised the volume of data
distributed through the internet. As an effect, a majority of digital resources have been …

This paper evaluates the performance of long short-term memory recurrent neural networks
(LSTM-RNN) on classifying intrusion detection data. LSTM networks can learn memory and …

Gated Recurrent Unit (GRU) is a recently-developed variation of the long short-term memory
(LSTM) unit, both of which are variants of recurrent neural network (RNN). Through empirical …

In recent years, the spike in the amount of information transmitted through communication
infrastructures has increased due to the advances in technologies such as cloud computing …

We claim that modelling network traffic as a time series with a supervised learning approach,
using known genuine and malicious behaviour, improves intrusion detection. To …

Intrusion detection plays an important role in ensuring information security, and the key
technology is to accurately identify various attacks in the network. In this paper, we explore …

In recent years, advancements in the field of the artificial intelligence (AI) gained a huge
momentum due to the worldwide appliance of this technology by the industry. One of the …

Software‐defined networking (SDN) is a promising approach to networking that provides an
abstraction layer for the physical network. This technology has the potential to decrease the …