Ontology analysis has been shown to be an effective first step in the construction of robust knowledge based system. Moreover, the popularity of semantic technologies and the semantic web has provided several beneficial opportunities for the modeling and computer security communities of interest. This paper describes the role of ontologies in facilitating network security modeling. It outlines the technical challenges in distributed network security simulation modeling and describes how ontology-based methods may be applied to address these challenges. The paper concludes by describing an ontology-based solution framework for network security simulation modeling and analysis and outlining the benefits of this solution approach.

Worms have become a real threat for computer users for the past few years. Worm is more prevalent today than ever before, and both home users and system administrators need to be on the alert to protect their network or company against attacks. It is coming out so fast these days that even the most accurate scanners cannot track all of the new ones. Indeed until now there is no specific way to classify the worm. To understand the threats posed by the worms, this research had been carried out. In this paper the researchers proposed a new way to classify the worms which later is used as the basis to build up a system which is called as the EDOWA system to detect worms attack. Details on how the new worm of classification which is called as EDOWA worm classification is produced are explained in this paper. Hopefully this new worm classification can be used as the basis model to produce a system either to detect or defend organization from worms attack.

Computer viruses have received a lot of attention. In fact, the best-known viruses have not been viruses at all, but worms, programs that spread through networks instead of modifying programs. Both viruses and worms reproduce themselves and defensive measures have focused on stopping or slowing their spread. Ultimately, though, there is no defense better than a comprehensive security strategy that embraces user education, crisis-response teams, and technologically sound security measures including, but not limited to, those that relate specifically to the threats posed by viruses and worms. Defense against harm can consist of preventing the harm from occurring, limiting the extent of the harm, or recovering from the harm after it has occurred. This research aims to resolve the confusion in identifying visualization, simulation and games in teaching malware analysis. Computer simulation has greater impact and based on research that had been carried out it is identified as one of the best approach in teaching worm analysis.