Skip to main content
Disciplines
Automotive Business IT + Informatics Construction + Real Estate Electrical Engineering + Electronics Energy + Sustainability Insurance + Risk Finance + Banking Management + Leadership Marketing + Sales Mechanical Engineering + Materials
Events
DE
EN
Books
Journals
Topic Page
Marketing
Start single access now
Access for companies
EXTENDED SEARCH
Log in
Top
Published in:
Introduction Read chapter Read first chapter

2020 | OriginalPaper | Chapter

3. Aiding Data-Driven Attack Model with a Compiler Modification

Authors : Sujit Rokka Chhetri, Mohammad Abdullah Al Faruque

Published in: Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

Publisher: Springer International Publishing

Log in

Activate our intelligent search to find suitable subject content or patents.

search-config
loading …

Abstract

In previous chapter, we presented a data-driven acoustic attack model. However, in the previous attack model, an attacker may be far from being able to completely reconstruct the G/M-code due to lack of enough information leakage through the side-channels. In this chapter, we present a novel way to amplify the information leakage and thus boost the chances of recovery of G/M-code by surreptitiously altering the compiler. By using this compiler, an adversary may easily control various parameters to magnify the leakage of information from a 3D printer while still producing the desired object, thus remaining hidden from the authentic users. This type of attack may be implemented by strong attackers having access to the tool chain and seeking high level of stealth. We present an implementation of such a compiler here and demonstrate how it can increase the success rate of recovering G/M-codes from the four side-channels (acoustic, power, vibration, and electromagnetic) by up to 39% compared to previously proposed data-driven attack model.

Dont have a licence yet? Then find out more about our products and how to get one now:

Springer Professional "Wirtschaft+Technik"

Online-Abonnement

Mit Springer Professional "Wirtschaft+Technik" erhalten Sie Zugriff auf:

  • über 102.000 Bücher
  • über 537 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Maschinenbau + Werkstoffe
  • Versicherung + Risiko

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Technik"

Online-Abonnement

Mit Springer Professional "Technik" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 390 Zeitschriften

aus folgenden Fachgebieten:

  • Automobil + Motoren
  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Elektrotechnik + Elektronik
  • Energie + Nachhaltigkeit
  • Maschinenbau + Werkstoffe




 

Jetzt Wissensvorsprung sichern!

inform now

Springer Professional "Wirtschaft"

Online-Abonnement

Mit Springer Professional "Wirtschaft" erhalten Sie Zugriff auf:

  • über 67.000 Bücher
  • über 340 Zeitschriften

aus folgenden Fachgebieten:

  • Bauwesen + Immobilien
  • Business IT + Informatik
  • Finance + Banking
  • Management + Führung
  • Marketing + Vertrieb
  • Versicherung + Risiko




Jetzt Wissensvorsprung sichern!

inform now
previous chapter Data-Driven Attack Modeling Using Acoustic Side-Channel
next chapter Data-Driven Defense Through Leakage Minimization
Literature
1.
Lee, J., et al. (2015). A cyber-physical systems architecture for industry 4.0-based manufacturing systems. Manufacturing Letters, 3, 18–23.CrossRef
2.
Lee, E. A. (2008). Cyber physical systems: Design challenges. In 2008 11th IEEE international symposium on object oriented real-time distributed computing (ISORC). Piscataway: IEEE.
3.
Chhetri, S. R., Wan, J., & Al Faruque, M. A. (2017). Cross-domain security of cyber-physical systems. In 2017 22nd Asia and South Pacific design automation conference (ASP-DAC). Piscataway: IEEE.
4.
Cardenas, A., et al. (2009). Challenges for securing cyber physical systems. In Workshop on future directions in cyber-physical systems security.
5.
Wu, G., et al. (2016). A survey on the security of cyber-physical systems. Control Theory and Technology, 14(1), 2–10.MathSciNetCrossRef
6.
Zeltmann, S. E., Gupta, N., et al. (2016). Manufacturing and security challenges in 3D printing. Jom, 68(7), 1872–1881.CrossRef
7.
Chhetri, S. R., & Al Faruque, M. A. (2017). Side-channels of cyber-physical systems: Case study in additive manufacturing. IEEE Design & Test, 34(4), 18–25.CrossRef
8.
Yampolskiy, M., Andel, T. R., et al. (2014). Intellectual property protection in additive layer manufacturing: Requirements for secure outsourcing. In Proceedings of the 4th Program Protection and Reverse Engineering Workshop. New York: ACM.
9.
Sturm, L., Williams, C., Camelio, J., et al. (2014). Cyber-physical vulnerabilities in additive manufacturing systems. Context, 7(2014), 8.
10.
Guri, M., Zadov, B., Atias, E., & Elovici, Y. (2017). LED-it-go: Leaking (a lot of) data from air-gapped computers via the (small) hard drive led. arXiv preprint:1702.06715.
11.
Lin, L., Kasper, M., Güneysu, T., Paar, C., & Burleson, W. (2009). Trojan side-channels: Lightweight hardware Trojans through side-channel engineering. In CHES (Vol. 5747, pp. 382–395). Cham: Springer.
12.
Hojjati, A., Adhikari, A., et al. (2016). Leave your phone at the door: Side channels that reveal factory floor secrets. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. New York: ACM.
13.
Song, C., Lin, F., et al. (2016). My smartphone knows what you print: Exploring smartphone-based side-channel attacks against 3D printers. In Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. New York: ACM.
14.
Al Faruque, M. A., Chhetri, S. R., et al. (2016). Acoustic side-channel attacks on additive manufacturing systems. In International Conference on Cyber-Physical Systems (ICCPS). Piscataway: IEEE.
15.
16.
Al Faruque, M.A., Chhetri, S. R., Faezi, S., & Canedo, A. (2016). Forensics of thermal side-channel in additive manufacturing systems-semantic scholar. Irvine, CA.
17.
Liaw, A., & Wiener, M. (2002). Classification and regression by randomForest. R News, 2(3), 18–22.
18.
Haykin, S., & Network, N. (2004). A comprehensive foundation. Neural Networks, 2(2004), 41.
19.
Becker, G. T., Regazzoni, F., Paar, C., & Burleson, W. P. (2013). Stealthy dopant-level hardware Trojans. In International Workshop on Cryptographic Hardware and Embedded Systems (pp. 197–214). Berlin: Springer.
20.
Potkonjak, M. (2010). Synthesis of trustable ICs using untrusted CAD tools. In 2010 47th ACM/IEEE Design Automation Conference (DAC) (pp. 633–634). Piscataway: IEEE.
21.
22.
23.
24.
25.
26.
27.
Swierczynski, P., Fyrbiak, M., Koppe, P., Moradi, A., & Paar, C. (2016). Interdiction in practice: hardware Trojan against a high-security USB flash drive. Journal of Cryptographic Engineering, 7(3), 1–13.
28.
Chari, S., Rao, J. R., & Rohatgi, P. (2002). Template attacks. In International workshop on cryptographic hardware and embedded systems. Berlin: Springer.
29.
Hospodar, G., Gierlichs, B., De Mulder, E., Verbauwhede, I., & Vandewalle, J. (2011). Machine learning in side-channel analysis: A first study. Journal of Cryptographic Engineering, 1(4), 293–302.CrossRef
30.
31.
Belikovetsky, S., Yampolskiy, M., et al. (2016). dr0wned-cyber-physical attack with additive manufacturing. arXiv preprint:1609.00133.
Metadata
Title
Aiding Data-Driven Attack Model with a Compiler Modification
Authors
Sujit Rokka Chhetri
Mohammad Abdullah Al Faruque
Copyright Year
2020
Book
Data-Driven Modeling of Cyber-Physical Systems using Side-Channel Analysis

Print ISBN: 978-3-030-37961-2

Electronic ISBN: 978-3-030-37962-9

Copyright Year: 2020

DOI
https://doi.org/10.1007/978-3-030-37962-9_3