Techniques to detect anomalies (IDS)

Susheela Sarasamma, Julie Huff, "Anomaly based techniques for intrusion detection systems", Northrop Grumman Mission Systems
In this presentation, the authors provide information on the various anomaly based techniques which can be used for the IDS.
General anomaly based techniques include, statistical, neural network and machine learning.

The authors have specifically discussed a couple of anomaly detection techniques for an IDS which include the following
1. A novel anomaly detection technique using Kohonen network
2. Conclusions on the test conducted on multi-level k map

Kinds of anomalies to be considered as outliers include the following
1. outlier detection
2. novelty detection
3. noice detection
4. deviation detection
5. exception mining

* Now suppose we have to come up with efficient testing techniques for anomaly based intrusion detection systems there are set of things which we might want to understand

- study the different anomaly based intrusion detection systems. As the test methodology might vary depending on the technique which has been adopted.

- research on the platform which might be required for performing the testing for such a system.

- in addition we might have to come to a decision or rather the focus of the research

- we might also want to understand the typical attacks in the case of the anomaly based intrusions

- audit trails how are they being used for testing purposes

- if we need to compose of a testing methodology, then how should the evaluation be done for it