Yusuf Sani

The rise in demand for real-time applications on the Internet necessitates Quality of Service (QoS). Differentiated Services (DiffServ) is one of the technologies used currently to provide QoS and service differentiation. It is simple and scalable. It provides service differentiation to aggregates, mainly through the Assured Forwarding (AF) per-hop behaviour. Previous work on fair sharing of network bandwidth did not adequately address the Under-Provisioned Network (UPN) condition. In this paper, we propose a new three-colour marker, named paItswTCM (provision-aware Improved TSW based Three-Colour Marker). We compare our new algorithm with both time-sliding window markers and token-bucket-based markers using simulations. Results show that our new provision-aware marker outperforms these previous algorithms not only in the UPN condition but also for low to medium network provision levels. We conclude that to achieve proportional sharing of bandwidth, no packet type should be injected at the expense of others.

With the increasing number of computers being connected to the Internet, security of an information system has never been more urgent. Because no system can be absolutely secure, the timely and accurate detection of intrusions is necessary. This is the reason of an entire area of research, called Intrusion Detection Systems (IDS). Anomaly systems detect intrusions by searching for an abnormal system activity. But the main problem of anomaly detection IDS is that; it is very difficult to build, because of the difficulty in defining what is normal and what is abnormal. Neural network with its ability of learning has become one of the most promising techniques to solve this problem. This paper presents an overview of neural networks and their use in building anomaly intrusion systems.