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  1. As data-intensive science becomes the norm in many fields of science, high-performance data transfer is rapidly becoming a core scientific infrastructure requirement. To meet such a requirement, there has been a rapid growth across university campus to deploy Science DMZs. However, it is challenging to efficiently monitor the traffic in Science DMZ because traditional intrusion detection systems (IDSes) are equipped with deep packet inspection (DPI), which is resource-consuming. We propose to develop a lightweight side-channel based anomaly detection system for traffic winnowing to reduce the volume of traffic finally monitored by the IDS. We evaluate our approach based on the experiments in a Science DMZ environment. Our evaluation demonstrates that our approach can significantly reduce the resource usage in traffic monitoring for Science DMZ. 
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