  A Network Intrusion Detection System (NIDS) is a network security technology
for detecting intruder attacks. However, it produces a great amount of
low-level 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 the 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 datasets, which are DARPA 2000, and ISCX2012.
The Completeness and Soundness of the proposed model are measured to evaluate
the overall correlation effectiveness.
