Intrusion Detection Based On Artificial Intelligence Technique

Information Technology has become a main and important component to support critical infrastructure services in various sectors of our society. It is being used for sharing information and various operations. Many organizations are used to create complex network systems to give supply to the users. So due to this rapid expansion of computer usage, the security of the system has become very important. On every new day, a new kind of attack is being faced by the organizations. There were many methods which have being proposed for the development in the field of intrusion detection using artificial intelligence techniques. In this paper, we will have a look on a technique: K-Nearest Neighbors Algorithm for the understanding Intrusion Detection System. K-Nearest-Neighbors is one of the simplest and effective classification methods. This research shows the performance of the techniques on various test data sets. And the accuracy rate and the error rate are being calculated for these test data sets. And Confusion Matrix has been created for different Test Datasets for different values of K. Here, a model is being developed or the detection of anomaly attacks.