Leave Your Phone at the Door: Side Channels that Reveal Factory Floor Secrets
Leave Your Phone at the Door: Side Channels that Reveal Factory Floor Secrets
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DOI：
10.1145/2976749.2978323
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发表时间：
2016-10
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影响因子：
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通讯作者：
Avesta Hojjati;Anku Adhikari;Katarina Struckmann;Edward Chou;Thi Ngoc Tho Nguyen;Kushagra Madan;M. Winslett;Carl A. Gunter;William P. King
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文献类型：
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作者：
Avesta Hojjati;Anku Adhikari;Katarina Struckmann;Edward Chou;Thi Ngoc Tho Nguyen;Kushagra Madan;M. Winslett;Carl A. Gunter;William P. King
从铅笔到商用飞机，每一件人造物品都必须经过设计和制造。当偷窃一项设计或制造工艺规范比发明自己的设计或制造工艺规范更便宜或更容易时，偷窃的动机就出现了。随着越来越多的制造业数据上网，此类盗窃事件也在增加。在本文中，我们提出了一种对制造设备的侧信道攻击，它揭示了产品的形式及其制造过程，即，它到底是怎么做的在攻击中，一个人故意或意外地将一个支持攻击的电话靠近设备，或者在附近的任何电话上拨打或接听电话。执行攻击的手机记录音频，并可选地记录磁力计数据。我们提出了一种基于机器学习、信号处理和人工辅助的方法，从捕获的数据中重建产品的形式和制造过程。我们演示了对3D打印机和CNC铣床的攻击，每台机器都有自己的声学特征，并讨论了这两种不同机器捕获的传感器数据的共性。我们比较了各种智能手机型号捕获的数据质量。从3D打印机捕获数据，我们再现了重建者以前未知的物体的形状和过程信息。平均而言，我们的精度是在1毫米内重建一个线段的长度在一个制造的对象的形状和1度内确定一个角度在一个制造的对象的形状。最后，我们提出了防御这些攻击的建议。
From pencils to commercial aircraft, every man-made object must be designed and manufactured. When it is cheaper or easier to steal a design or a manufacturing process specification than to invent one's own, the incentive for theft is present. As more and more manufacturing data comes online, incidents of such theft are increasing. In this paper, we present a side-channel attack on manufacturing equipment that reveals both the form of a product and its manufacturing process, i.e., exactly how it is made. In the attack, a human deliberately or accidentally places an attack-enabled phone close to the equipment or makes or receives a phone call on any phone nearby. The phone executing the attack records audio and, optionally, magnetometer data. We present a method of reconstructing the product's form and manufacturing process from the captured data, based on machine learning, signal processing, and human assistance. We demonstrate the attack on a 3D printer and a CNC mill, each with its own acoustic signature, and discuss the commonalities in the sensor data captured for these two different machines. We compare the quality of the data captured with a variety of smartphone models. Capturing data from the 3D printer, we reproduce the form and process information of objects previously unknown to the reconstructors. On average, our accuracy is within 1 mm in reconstructing the length of a line segment in a fabricated object's shape and within 1 degree in determining an angle in a fabricated object's shape. We conclude with recommendations for defending against these attacks.