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Identification of Bot Commands by Run-Time Execution Monitoring

机译:通过运行时执行监视识别Bot命令

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Botnets pose serious threats to the Internet. In spite of substantial efforts to address the issue, botnets are dramatically spreading. Bots in a botnet execute commands under the control of the botnet owner or controller. A first step in protecting against botnets is identification of their presence, and activities. In this paper, we propose a method of identifying the high-level commands executed by bots. The method uses run- time monitoring of bot execution to capture and analyze run- time call behavior. We find that bots have distinct behavior patterns when they perform pre-programmed bot commands. The patterns are characterized by sequences of common API calls at regular intervals. We demonstrate that commands aiming to achieve the same result have very similar API call behavior in bot variants, even when they are from different bot families. We implemented and evaluated a prototype of our method. Run-time monitoring is accomplished by user-level hooking. In the experiments, the proposed method successfully identified the bot commands being executed with a success rate of 97%. The ability of the method to identify bot commands despite the use of execution obfuscation is also addressed.
机译:僵尸网络对互联网构成了严重威胁。尽管为解决该问题付出了巨大的努力,僵尸网络仍在迅速传播。僵尸网络中的僵尸程序在僵尸网络所有者或控制器的控制下执行命令。防范僵尸网络的第一步是识别僵尸网络的存在和活动。在本文中,我们提出了一种识别由机器人执行的高级命令的方法。该方法使用对机器人执行的运行时监视来捕获和分析运行时调用行为。我们发现,机器人在执行预先编程的机器人命令时具有不同的行为模式。这些模式的特征是定期按常规API调用序列进行。我们证明了旨在实现相同结果的命令在Bot变体中具有非常相似的API调用行为,即使它们来自不同的Bot家族。我们实现并评估了该方法的原型。运行时监视是通过用户级挂钩完成的。在实验中,提出的方法成功识别出正在执行的机器人命令,成功率为97%。尽管解决了执行混淆的问题,该方法仍然能够识别机器人命令。

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