Computer Science

Browse

Now showing 1 - 1 of 1

AN IMPROVED ARTIFICIAL INTELLIGENCE MODEL FOR CYBER SECURITY INCIDENT RESPONSE AND RECOVERY SYSTEM
(2024) ASIMI OLALEKAN IDRIS
Cyber security incident response and recovery systems are currently facing a number of challenges that are different from the fast growth of advanced cyber threats to the complexity faced in coordinating an effective response across the various technological environments. Several techniques have been developed, but there are problems in the detection and mitigation of emerging threats in real-time, thus, organizations are at risk of data breaches, financial losses, and reputational damage. This study presents an improved Artificial Intelligence model that assists in effective incidence response and recovery from previously known and unknown threats. The bagging ensemble approach is adopted using Naïve Bayes, Decision Tree, Support Vector Machine and Neural Network as base classifiers to form the model. In the experiment, the dataset used has a total of 22544 instances and 42 attributes. The result gives 98.69% accuracy with ROC and PRC Area both 0.999. The Recall and F-Measure are both 0.987.