Global Intrusion Detection Environments and Platform for Anomaly-Based Intrusion Detection Systems

The defense is the critical element of the computer system, and the most challenging issues are detecting the intrusion attacks. The IDS is the most critical cyber-security factor which can detect intrusion before, during, and after an attack. This paper provides an overall IDS benchmarking which quantifies different IDS properties, types of anomaly-based IDS that are deployed in different environments or platforms, and comparison among them based on methods used, their details, and advantages of each method. We have analyzed the different IDS techniques based on anomaly and various issues associated with anomaly-based IDSs. We addressed global environments for intrusion detection and framework for behavioral or anomaly-based intrusion detection systems and discussed the challenges facing anomaly-based IDSs. After reviewing the various anomaly-based IDS techniques, we have analyzed that successful detection rates could not be achieved by a single technique. To lower the false prediction rate and decreased the complexity of the process, an efficient automated hybrid technique is suggested for achieving accurate detection rates to enhance anomaly detection.