Intrusion detection systems (IDS) are special computer security tools which help detect intrusion attempts. Misuse based detection is one of the techniques which is used by IDS to recognize predefined attack signatures. Attack languages, also known as detection languages, are used to describe attack signatures. Detection languages should be simple, expressive and flexible enough to help encode ...

First, this case study explores an Intrusion Detection System package called Snort (provided by Cisco Systems) in a cloud environment. Snort is an open source and highly scalable signaturebased intrusion detection system. Here, Snort is deployed on Ubuntu Server 16.0.4 running on a virtual machine within a Microsoft Azure cloud system. This paper provides details on installing Snort on the virt...

With the thriving technology and the great increase in the usage of computer networks, the risk of having these network to be under attacks have been increased. Number of techniques have been created and designed to help in detecting and/or preventing such attacks. One common technique is the use of Intrusion Detection Systems (IDS). Today, number of open sources and commercial IDS are availabl...

The basic task in intrusion detection system is to classify network activities as normal or abnormal while minimizing misclassification. In literature, various machine learning and data mining techniques have been applied to Intrusion Detection Systems (IDSs) to protect the special computer systems, vulnerable traffics cyber-attacks for computer networks. In addition, Support Vector Machine (SV...

Computer security is defined as the protection of computing systems against threats to confidentiality, integrity, and availability. An intrusion is defined as any set of actions that attempt to compromise the integrity, confidentiality or availability of a resource. The process of monitoring the events occurring in a computer system or network and analyzing them for sign of intrusions is known...

Most of the current Intrusion Detection Systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything) to the detection process. The purpose of this study is to identify important input features in building an IDS that is computationally efficient and effective. We investigated the performance of two featu...

Assuring secure and reliable operation of networks has become a priority research area these days because of ever growing dependency on network technology. Intrusion detection systems (IDS) are used as the last line of defense. Intrusion Detection System identifies patterns of known intrusions (misuse detection) or differentiates anomalous network data from normal data (anomaly detection). In t...

Recently data mining methods have gained importance in addressing network security issues, including network intrusion detection-a challenging task in network security. Intrusion detection systems aim to identify attacks with a high detection rate and a low false alarm rate. Intrusion Detection System (IDS) and Intrusion Prevention Systems (IPS) in computer network security are real-time softwa...

Current intrusion detection systems (IDS) examine all data features to detect intrusion or misuse patterns. Some of the features may be redundant or contribute little (if anything) to the detection process. The purpose of this study is to identify important input features in building an IDS that is computationally efficient and effective. We investigated the performance of two feature selection...

Over the past decade Intrusion Detection Systems (IDS) have been steadily improving their efficiency and effectiveness in detecting attacks. This is particularly true with signature-based IDS due to progress in attack analysis and attack signature specification. At the same time system complexity, overall numbers of bugs and security vulnerabilities have increased. This has led to the recogniti...