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This paper addresses the problem of reasoning about relations between network packets on a host or in a network. Our analysis approach is to discover the causal relations among network packets, and use the relational structure of network events to identify anomalous activities that cannot be attributed to a legitimate cause. The key insight that motivates our traffic-analysis approach is that higher-order information such as the underlying relations of events is useful for human experts'doi:10.1145/2508859.2512504 dblp:conf/ccs/ZhangYR13 fatcat:dwtwspcycrbhhcrvfpye6yqes4