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Mitigating distributed denial-of-service attacks can be a complex task due to the wide range of attack types, attacker adaptation, and defender constraints. We propose a defense mechanism which is largely automated and can be implemented on current software defined networking (SDN)-enabled networks. Our mechanism combines normal traffic learning, external(More)
The existing body of research on malware simulation does not make full use of the topological and geographic location of the simulated malware-infected computers on the internet. We address this issue for creating a topologically-aware framework for modeling the spread of malware. Our framework can accommodate a variety of infection models, as well as(More)
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