Intrusion classification using ECLAT and Fuzzy Logic

Abstract

In today's world with the increase in internet usage, every digital gadget is getting connected to the internet. Due to the open connectivity of the internet, devices connected to the internet are exposed to the disturbances caused by masqueraders, misfeasors, malware writers, and intruders. Researchers are in the continuous search of methods to detect the attacks in the network and to introduce these methods to the low computation capability devices. In this work, it aimed at creating a disruption sensing system for identifying the disturbances caused by intruders. It will be achieved by choosing the best traffic capturing component. Then, by introducing/improving the association rule mining algorithm to identify the patterns in the data and to generate better rules. Then, by using the proposed method based on fuzzy logic and inference system to help in identifying the attack.