The rise in computer networks and internet attacks has become alarming for most service
providers. It has triggered the need for the development and implementation of intrusion …

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

Network intrusion detection systems play an important role in protecting the network from
attacks. However, Existing network intrusion data is imbalanced, which makes it difficult to …

Recently, Convolutional neural network (CNN) architectures in deep learning have achieved
significant results in the field of computer vision. To transform this performance toward the …

Due to the massive amount of the network traffic, attackers have a great chance to cause a
huge damage to the network system or its users. Intrusion detection plays an important role …

With the rapid advancements of ubiquitous information and communication technologies, a
large number of trustworthy online systems and services have been deployed. However …

Abstract Machine-learning techniques have been actively employed to information security
in recent years. Traditional rule-based security solutions are vulnerable to advanced attacks …

Companies in a wide variety of industries use the customer churn prediction (CCP) process
to keep their current clientele happy. Insurance companies need to be able to forecast churn …

In computer security, designing a robust intrusion detection system is one of the most
fundamental and important problems. In this paper, we propose a system-call language …

An intrusion detection system (IDS) identifies whether the network traffic behavior is normal
or abnormal or identifies the attack types. Recently, deep learning has emerged as a …