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对HTTP请求因果关系推理

Towards Sound HTTP Request Causation Inference

作者:Kristin Stephens 作者单位:Electrical Engineering and Computer Sciences University of California at Berkeley 加工时间:2013-11-23 信息来源:EECS 索取原文[19 页]
关键词:网络跟踪;HTTP请求;控制数据样本
摘 要:Network traces are a useful tool in understanding how users navigate the web. Knowing the sequence of pages that led a user to arrive at a malicious website can help researchers develop techniques to prevent users from reaching such sites. Nevertheless, inferring sound causation between HTTP requests is a challenging task. We present here methods for and considerations when inferring causation relationships betweenHTTP requests. We also introduce causation trees and terminology needed to model causal relationships between HTTP requests. Finally, we describe Gretel, our system that infers causation relationships, how we calibrated it, and our results on a sample control data set where ground truth was available.
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