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Characterizing industrial control system devices on the Internet

机译:在互联网上表征工业控制系统设备

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Industrial control system (ICS) devices with IP addresses are accessible on the Internet and play a crucial role for critical infrastructures like power grid. However, there is a lack of deep understanding of these devices' characteristics in the cyberspace. In this paper, we take a first step in this direction by investigating these accessible industrial devices on the Internet. Because of critical nature of industrial control systems, the detection of online ICS devices should be done in a real-time and non-intrusive manner. Thus, we first analyze 17 industrial protocols widely used in industrial control systems, and train a probability model through the learning algorithm to improve detection accuracy. Then, we discover online ICS devices in the IPv4 space while reducing the noise of industrial honeypots. To observe the dynamics of ICS devices in a relatively long run, we have deployed our discovery system on Amazon EC2 and detected online ICS devices in the whole IPv4 space for eight times from August 2015 to March 2016. Based on the ICS device data collection, we conduct a comprehensive data analysis to characterize the usage of ICS devices, especially in the answer to the following three questions: (1) what are the distribution features of ICS devices, (2) who use these ICS devices, and (3) what are the functions of these ICS devices.
机译:具有IP地址的工业控制系统(ICS)设备可在Internet上访问,并为Power Grid等关键基础架构发放至关重要的作用。然而,缺乏对网络空间中这些设备的特征的深刻理解。在本文中,我们通过在互联网上调查这些可访问的工业设备来朝着这个方向迈出第一步。由于工业控制系统的批判性质,因此应以实时和非侵入方式进行在线ICS设备的检测。因此,我们首先通过学习算法分析在工业控制系统中广泛应用的17个工业协议,并通过学习算法训练概率模型,以提高检测精度。然后,我们发现IPv4空间中的在线ICS设备,同时减少了工业蜜罐的噪音。要在相对长的运行中观察ICS设备的动态,我们已在Amazon EC2上部署我们的发现系统,并在2015年8月至2016年3月从整个IPv4空间中检测到整个IPv4空间的在线ICS设备。基于ICS设备数据收集,我们进行全面的数据分析,以表征ICS设备的使用,尤其是在以下三个问题的答案中:(1)使用这些ICS设备的ICS设备的分布功能是什么?(3)是这些ICS设备的功能。

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