Prediction of Network Attacks

		Predictability of network state has received a considerable attention in many domains, including adaptive applications, congestion control, admission control, wireless and network management. Although in the past decade a range of prediction algorithms have proposed, they generally present isolated efforts focused of various traffic characteristics and do not constitute a systematic approach to prediction of network state.
Current Members:		Natalia Stakhanova
Previous Members:		Mahsa Kiani

Overview

The focus of this project is the comprehensive framework for prediction of network state. Essentially this network prediction framework should address two types of analysis:

• Simple forecasting such as forecasting of the network traffic volume.
• Advanced forecasting which is a more sophisticated prediction of the future network state. It allows to analyze potential bottlenecks of the network,  predict possible attacks,  show administrator potential problem spots, etc.