Improve the Firewall Accuracy By using Dynamic Ontology

Abstract

Data is considered an important asset for organizations, companies, and even people. Crucial decisions depend mainly on data. Exchanging data is essential in order to negotiate ideas, thoughts, and decisions. Networks are the communication channels of data exchange although data is exposed to different attacks, threats, and loss. Because of this, data security has become a key concern for different parties through their daily data manipulation. There are different ways to ensure data security. Paying attention to network threats, data encryption, and using strong passwords are all examples. However, a firewall represents the first defense line against malicious traffic throughout the network. Firewalls have a set of rules to be applied in the time of data exchange between inside and outside of data networks. Some of the firewalls apply such rules in a sequential manner, which degrades the performance of the firewall. In this work, we are utilizing a dynamic ontology of different firewall rules managed by SPARQL queries, so that the rules are applied faster, and thus, increasing the firewall performance. Experimental results show that our proposed methodology totally eliminates the anomalies in the firewall rules as a result of conducting longest matching with proper rules from the dynamically constructed ontology.