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Leave Your Phone at the Door: Side Channels that Reveal Factory Floor Secrets

Published: 24 October 2016 Publication History

Abstract

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.

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cover image ACM Conferences
CCS '16: Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security
October 2016
1924 pages
ISBN:9781450341394
DOI:10.1145/2976749
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than the author(s) must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected].

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Publication History

Published: 24 October 2016

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Author Tags

  1. cyber-physical systems
  2. data security for manufacturing
  3. side channels

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CCS '16 Paper Acceptance Rate 137 of 831 submissions, 16%;
Overall Acceptance Rate 1,261 of 6,999 submissions, 18%

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ACM SIGSAC Conference on Computer and Communications Security
October 14 - 18, 2024
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  • (2024)Extracting Payment Tokens Out of Sounds Produced by Magnetic Field FluctuationsIEEE Transactions on Mobile Computing10.1109/TMC.2024.335926623:9(8803-8821)Online publication date: Sep-2024
  • (2024)Secure Storage of Crypto Wallet Seed Phrase Using ECC and Splitting TechniqueIEEE Open Journal of the Computer Society10.1109/OJCS.2024.33987945(278-289)Online publication date: 2024
  • (2024)Shells Bells: Cyber-Physical Anomaly Detection in Data CentersNOMS 2024-2024 IEEE Network Operations and Management Symposium10.1109/NOMS59830.2024.10575124(1-10)Online publication date: 6-May-2024
  • (2024)Ensuring additive manufacturing quality and cyber–physical security via side-channel measurements and transmissionsJournal of Manufacturing Systems10.1016/j.jmsy.2024.02.00573(275-286)Online publication date: Apr-2024
  • (2023)Data Security in Additive ManufacturingAdditive Manufacturing Design and Applications10.31399/asm.hb.v24A.a0006962(203-209)Online publication date: 30-Jun-2023
  • (2023)Security Analysis of the 3MF Data FormatProceedings of the 26th International Symposium on Research in Attacks, Intrusions and Defenses10.1145/3607199.3607216(179-194)Online publication date: 16-Oct-2023
  • (2023)Re-Envisioning Industrial Control Systems Security by Considering Human Factors as a Core Element of Defense-in-Depth2023 IEEE European Symposium on Security and Privacy Workshops (EuroS&PW)10.1109/EuroSPW59978.2023.00048(379-385)Online publication date: Jul-2023
  • (2023)SOK: Side Channel Monitoring for Additive Manufacturing - Bridging Cybersecurity and Quality Assurance Communities2023 IEEE 8th European Symposium on Security and Privacy (EuroS&P)10.1109/EuroSP57164.2023.00071(1160-1178)Online publication date: Jul-2023
  • (2023)Security Threats in AMSpringer Handbook of Additive Manufacturing10.1007/978-3-031-20752-5_19(303-315)Online publication date: 18-Oct-2023
  • (2022)Study and Application of Machine Learning Methods in Modern Additive Manufacturing ProcessesApplications of Artificial Intelligence in Additive Manufacturing10.4018/978-1-7998-8516-0.ch004(75-95)Online publication date: 2022
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