Large-scale evaluation of distributed attack detection
Proceedings of the 2nd International Conference on Simulation Tools and Techniques
Distributed detection of large-scale attacks in the internet
CoNEXT '08 Proceedings of the 2008 ACM CoNEXT Conference
Anomaly-based identification of large-scale attacks
GLOBECOM'09 Proceedings of the 28th IEEE conference on Global telecommunications
Policy-driven network simulation: a resilience case study
Proceedings of the 2011 ACM Symposium on Applied Computing
Towards the simulation of energy-efficient resilience management
Proceedings of the 4th International ICST Conference on Simulation Tools and Techniques
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Distributed Denial-of-Service attacks pose unpredictable threats to the internet infrastructure and internet-based business. Thus, many attack detection systems and anomaly detection methods were developed in the past. A realistic evaluation of these mechanisms and comparable results, however, are impossible up to now. Furthermore, an adaptation to new situations or an extension of existing systems in most cases is complex and time-consuming. Therefore, we developed a framework for attack detection which allows for an integration of various detection methods as lightweight modules. These modules can be combined easily and arbitrarily and thus, adapted to varying situations. Additionally, our framework can be applied in different runtime environments transparently. This enables an easy evaluation with meaningful and comparable results based on realistic large-scale scenarios, e.g. by using a network simulator.