In this paper, Big Data and Deep Learning Techniques are integrated to improve the
performance of intrusion detection systems. Three classifiers are used to classify network …

This paper successfully tackles the problem of processing a vast amount of security related
data for the task of network intrusion detection. It employs Apache Spark, as a big data …

An intrusion detection system is a security system that aims to detect sabotage and
intrusions on networks to inform experts of the attack and abuse of the network. Different …

With the swift growth of Internet technology, various types of attacks and intrusions are taking
place over the Internet. Intrusion Detection Systems (IDS) are widely used to detect attacks …

In this study, we present a detailed analysis of deep learning techniques for intrusion
detection. Specifically, we analyze seven deep learning models, including, deep neural …

Study on intrusion detection system (IDS) mostly allow network administrators to focus on
development activities in terms of network security and making better use of resource. Many …

The use of deep learning models for the network intrusion detection task has been an active
area of research in cybersecurity. Although several excellent surveys cover the growing …

With the increment of cyber traffic, there is a growing demand for cyber security. How to
accurately detect cyber intrusions is the hotspot of recent research. Traditional Intrusion …

Many studies utilized machine learning schemes to improve network intrusion detection
systems recently. Most of the research is based on manually extracted features, but this …

In this paper, we present a survey of deep learning approaches for cyber security intrusion
detection, the datasets used, and a comparative study. Specifically, we provide a review of …