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 …

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 …

Due to increase in internet based services, the size of network traffic data has become so
large and complex that it is very difficult to process with the traditional data processing tools …

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 …

Nowadays, network intrusion is considered as one of the major concerns in network
communications. Thus, the developed network intrusion detection systems aim to identify …

The network intrusion detection system is an important tool for protecting computer networks
against threats and malicious attacks. Many techniques have recently been proposed; …

Recently, computer networks faced a big challenge, which is that various malicious attacks
are growing daily. Intrusion detection is one of the leading research problems in network …

With the rapid advancement in network technologies, the need for cybersecurity has gained
increasing momentum in recent years. As a primary defense mechanism, an intrusion …

A variety of attacks are regularly attempted at network infrastructure. With the increasing
development of artificial intelligence algorithms, it has become effective to prevent network …

Network intrusion detection is one of the most important parts for cyber security to protect
computer systems against malicious attacks. With the emergence of numerous sophisticated …