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Distributed denial of service (DDoS) attack is a critical threat to the Internet. Recently we have proposed the PacketScore scheme, a DDoS defense architecture that supports automated attack detection, on-line attack characterization and attack blocking. Its key idea is to use a statistics-based packet scoring mechanism to distinguish between legitimate and non-legitimate packets and discard packets based on the packet scores. In order for such an approach to work, we need to perform on-line traffic characterizations, and compare such characterizations with the nominal profiles (generated from past history or off-line analysis). The threshold used for the score-based selective packet discard decision is dynamically adjusted based on the score distribution of recent incoming packets. In our previous paper [Kim et al. 2004], we discuss how our proposed system performs in different attack scenarios. In this paper, we first give a brief review of the PacketScore approach and further elaborate on the transient performance under varying attack types and intensities, which may be exploited in more sophisticated attacks. We then show that PacketScore is well capable of blocking such sophisticated attacks by simply adjusting the measurement window time scale to closely track the attack profile.