The Protection of LAN Using Semantic Firewalls

The amount and diversity of malware keeps growing while the same basic attack techniques are being used. A firewall is a network security key component that filters inbound and outbound network packets as per predefined security rules. Even though firewalls are an effective defense against some attacks, they have security flaws that can be leveraged in other circumstances. In the present work, it is claimed that an ontology-based semantic firewall and machine learning algorithms can effectively enhance the firewall and protect the LAN. This paper proposes an ontology-based model for the semantic firewall as an effort to explore its effectiveness. The method used in this paper is based on Description Logic (DL) Reasoners, Ontology APIs, and Semantic Web Languages (OWL and SWRL). The proposed semantic firewall takes its decisions of anomalies detection based on a set of protection rules of the ontology-based model. As a result, the proposed approach achieves a detection accuracy of 93%. The conclusion is drawn that the presented ontology classifier gives an understandable model of a semantic firewall (SWF) that offers candid and human-interpretable decision rules, as with other machine learning models.