Intrusion Detection System using Self Organizing Maps

TLDR: An algorithm based on neural networks that are suitable for Intrusion Detection Systems (IDS) and the name is “Self Organizing Maps” (SOM), a promising technique which has been used in many classification problems.

Abstract: With the rapid expansion of computer usage and computer network the security of the computer system has became very important. Every day new kind of attacks are being faced by industries. Many methods have been proposed for the development of intrusion detection system using artificial intelligence technique. In this paper we will have a look at an algorithm based on neural networks that are suitable for Intrusion Detection Systems (IDS) [1] [2]. The name of this algorithm is “Self Organizing Maps” (SOM). Neural networks method is a promising technique which has been used in many classification problems. The neural network component will implement the neural approach, which is based on the assumption that each user is unique and leaves a unique footprint on a computer system when using it. If a user's footprint does not match his/her reference footprint based on normal system activities, the system administrator or security officer can be alerted to a possible security breach. At the end of the paper we will figure out the advantages and disadvantages of Self Organizing Maps and explain how it is useful for building an Intrusion Detection System.