Predicting Network Attacks Using Ontology-Driven Inference

Autor:	Salahi, Ahmad, Ansarinia, Morteza
Rok vydání:	2013
Předmět:	Computer Science - Artificial Intelligence Computer Science - Cryptography and Security Computer Science - Networking and Internet Architecture
Zdroj:	International Journal of Information and Communication Technology (IJICT), Volume 4, Issue 1, 2012
Druh dokumentu:	Working Paper
Popis:	Graph knowledge models and ontologies are very powerful modeling and re asoning tools. We propose an effective approach to model network attacks and attack prediction which plays important roles in security management. The goals of this study are: First we model network attacks, their prerequisites and consequences using knowledge representation methods in order to provide description logic reasoning and inference over attack domain concepts. And secondly, we propose an ontology-based system which predicts potential attacks using inference and observing information which provided by sensory inputs. We generate our ontology and evaluate corresponding methods using CAPEC, CWE, and CVE hierarchical datasets. Results from experiments show significant capability improvements comparing to traditional hierarchical and relational models. Proposed method also reduces false alarms and improves intrusion detection effectiveness. Comment: 9 pages
Databáze:	arXiv
Externí odkaz:	http://arxiv.org/abs/1304.0913 Zobrazit plný text záznamu View this record from Arxiv