An Effective Attack Scenario Construction Model based on Attack Steps and Stages Identification

Abstract

A Network Intrusion Detection System (NIDS) is a network security technology for detecting intruder attacks. However, it produces a great amount of lowlevel alerts which makes the analysis difficult, especially to construct the attack scenarios. Attack scenario construction (ASC) via Alert Correlation (AC) is important to reveal the strategy of attack in terms of steps and stages that need to be launched to make the attack successful. In most of the existing works, alerts are correlated by classifying the alerts based on the cause-effect relationship. However, the drawback of these works is the identification of false and incomplete correlations due to infiltration of raw alerts. To address this problem, this work proposes an effective ASC model to discover the complete relationship among alerts. The model is successfully experimented using two types of dataset, which are DARPA 2000, and ISCX2012. The Completeness and Soundness of the proposed model are measured to evaluate the overall correlation effectiveness.