Intra Firewall Anomaly Policies Detection in Cloud Environment Using Firewall Tree

Firewalls have been extensively utilized to protect private networks on the Internet. A firewall examines each incoming and outgoing packet before deciding to allow or reject it based on its policy. The effectiveness of the firewall’s specified policies has a major impact on how well the firewall protects security. Developing firewall rules in large-scale systems is challenging because as firewall policies increase, relationships among rules of identical or separate firewalls get complex. The managed network can easily be rendered inoperable by network attacks due to incorrect firewall rule configuration. Finding these rule anomalies is difficult, though, as it takes a lot of time. In this study, a firewall tree has been developed to detect anomalous rules in cloud settings, helping firewall administrators maintain the rules effectively and solving anomaly problems. This paper detects four firewall anomaly policies: Redundant, shadowing, correlation, and generalization. The three stages of the solution presented in this work are firewall tree generation, generalizing the structure of the anomaly rules, and identifying firewall anomaly rules. The findings of the experiments demonstrate that the model’s development motivates firewall administrators and experts to formulate important decisions to address anomaly rules.