Supervised learning and pattern recognition is a crucial area of research in information
retrieval, knowledge engineering, image processing, medical imaging, and intrusion …

The network intrusion detection techniques are important to prevent our systems and
networks from malicious behaviors. However, traditional network intrusion prevention such …

Intrusion detection is one of the major research problems in network security. It is the
process of monitoring and analyzing network traffic data to detect security violations. Mining …

Intrusion Detection is one of the most common approaches used in detecting malicious
activities in any network by analyzing its traffic. Machine Learning (ML) algorithms help to …

Increasing pollution is causing adverse environmental effects, leading to increased interest
in combating this issue. There has been a significant interest in minimizing the pollution …

Across the globe, billions of dollars are spending every year to provide security to the
network systems to prevent the intrusions. Some consider the disruption of the vital systems …

In this paper, an approach to protecting virtual machines (VMs) against denial of service
(DoS) attacks in a cloud environment is proposed. An open source cloud computing platform …

Network Security has become the key foundation with the tremendous increase in usage of
network-based services and information sharing on networks. Intrusion poses a serious risk …

In this paper we discuss and analyze some of the intelligent classifiers which allows for
automatic detection and classification of networks attacks for any intrusion detection system …

Network intrusions have become a significant threat in recent years as a result of the
increased demand of computer networks for critical systems. Intrusion detection system …