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 ontologybased 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. �2008 IEEE.

EDOWA system is a system that is capable to detect worm efficiently and provide an early warning to the system administrator. Worms are a major threat to Internet-connected hosts and networks and their nature of widespread epidemic spread needed to be detected quickly in order to contain its outbreak. In EDOWA, the frequency of network packet will be observed by the system. The wide spreading nature of worm will cause the network packet to be transfer massively over the network and cause the substantial increase in frequency. The threshold that detects the worm activity pattern will adjust accordingly to the increase of network traffic to accommodate high speed large network traffic. By having this threshold adjust accordingly, it will increase worm detection efficiency. With fuzzy logic, the degree of urgency of a warning can be defined. � 2008 IEEE.

In this paper, the author(s) propose a new technique in spam detection from another discipline and propose an implementation of the underlying algorithm based on FPGA. The choice of algorithm are Needleman-Wunsch that are previously used in bioinformatics. By using Needleman-Wunsch as the main engine, real network traffic will be used as query and compared with spam signature to detect the real spam. Needleman-Wunsch algorithm is one of the earliest algorithm from the family of dynamic programming in approximate string matching. Applying Needleman-Wunsch algorithm in FPGA will greatly speeds the performance of this algorithm in spam scanning as it operate in hardware level instead of software level. � 2008 University of Plymouth All rights reserved.

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. � 2009 Springer Netherlands.