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Low-storage capture and loss recovery selective replay of real flows

机译:低存储量捕获和丢失恢复,选择性重播实际流

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摘要

Capturing and replaying real flows are important for testing network security products. However, capturing real flows demands a high storage cost and runs a risk of capture loss, which makes the replay inaccurate. Replaying real flows should be accurate and stateful to adapt to the reaction of the device under test. It should also efficiently reproduce a defect and help developers identify the flows triggering defects. Therefore, this work first presents the (N, M, P) capture scheme which begins with, for each connection, capturing at most N bytes of application payload and then at most M bytes of application payload for at most each of the subsequent P packets in the same connection. This scheme reduces 87 percent of storage cost while retaining 99.74 percent of original events. This work develops a tool named SocketReplay with the mechanisms of loss recovery, stateful replay, and selective replay. Loss recovery tracks TCP sequence numbers to identify capture loss and recovers incomplete flows with dummy data. Stateful replay maintains the states in the TCP/IP stack to replay real flows. Selective replay incrementally selects flows to replay. The results show that SocketReplay can accurately and efficiently reproduce product events and significantly decrease the volume of replayed packet traces.
机译:捕获和重放真实流对于测试网络安全产品很重要。但是,捕获实际流需要高昂的存储成本,并存在捕获丢失的风险,这会使重放不准确。重播真实流量应准确且有状态,以适应被测设备的反应。它还应该有效地重现缺陷,并帮助开发人员识别触发缺陷的流程。因此,这项工作首先提出了(N,M,P)捕获方案,该方案从每个连接开始,捕获最多N个字节的应用程序有效负载,然后捕获最多M个字节的应用程序有效负载,用于后续的每个P数据包在相同的连接。该方案减少了87%的存储成本,同时保留了99.74%的原始事件。这项工作开发了一个名为SocketReplay的工具,该工具具有丢失恢复,有状态重播和选择性重播的机制。丢失恢复跟踪TCP序列号以识别捕获丢失并使用伪数据恢复不完整的流。有状态重播可维护TCP / IP堆栈中的状态以重播实际流。选择性重播以增量方式选择要重播的流。结果表明,SocketReplay可以准确有效地重现产品事件,并显着减少重播的数据包跟踪的数量。

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