10.1145/3243734.3243781acmconferencesArticle/Chapter ViewAbstractPublication PagesccsConference Proceedingsconference-collections
research-article
Open Access

Truth Will Out: Departure-Based Process-Level Detection of Stealthy Attacks on Control Systems

Authors Info & Claims
Online:15 October 2018Publication History

ABSTRACT

Recent incidents have shown that Industrial Control Systems (ICS) are becoming increasingly susceptible to sophisticated and targeted attacks initiated by adversaries with high motivation, domain knowledge, and resources. Although traditional security mechanisms can be implemented at the IT-infrastructure level of such cyber-physical systems, the community has acknowledged that it is imperative to also monitor the process-level activity, as attacks on ICS may very well influence the physical process. In this paper, we present PASAD, a novel stealthy-attack detection mechanism that monitors time series of sensor measurements in real time for structural changes in the process behavior. We demonstrate the effectiveness of our approach through simulations and experiments on data from real systems. Experimental results show that PASAD is capable of detecting not only significant deviations in the process behavior, but also subtle attack-indicating changes, significantly raising the bar for strategic adversaries who may attempt to maintain their malicious manipulation within the noise level.

Supplemental Material

p817-aoudi.mp4

References

  1. Ali Abbasi and Majid Hashemi. 2016. Ghost in the PLC Designing an Undetectable Programmable Logic Controller Rootkit via Pin Control Attack. Black Hat Europe (2016).Google ScholarGoogle Scholar
  2. Marshall Abrams and Joe Weiss. 2008. Malicious Control System Cyber Security Attack Case Studytextemdash Maroochy Water Services, Australia. McLean, VA: The MITRE Corporation (2008).Google ScholarGoogle Scholar
  3. Matthew Allen and Carlo Pisani. 2018. Hacking and Cyber Warfare are Top Humanitarian Concerns. https://www.swissinfo.ch/eng/peter-maurer_hacking-and-cyber-warfare-are-top-humanitarian-concerns/43847744. Last visited 2018-08-01.Google ScholarGoogle Scholar
  4. Magnus Almgren, Wissam Aoudi, Robert Gustafsson, Robin Krahl, and Andreas Lindhé. 2018. The Nuts and Bolts of Deploying Process-Level IDS in Real Control Systems. Technical Report. Chalmers University of Technology.Google ScholarGoogle Scholar
  5. Kaung Myat Aung. 2015. Secure Water Treatment Testbed (SWaT): An Overview. Technical Report. Singapore University of Technology and Design.Google ScholarGoogle Scholar
  6. George Box, Gwilym Jenkins, Gregory Reinsel, and Greta Ljung. 2015. Time Series Analysis: Forecasting and Control. John Wiley & Sons. Google ScholarGoogle ScholarDigital LibraryDigital Library
  7. David S Broomhead and Gregory P King. 1986. Extracting Qualitative Dynamics from Experimental Data. Physica D: Nonlinear Phenomena (1986). Google ScholarGoogle ScholarDigital LibraryDigital Library
  8. Alvaro Cárdenas, Saurabh Amin, Zong-Syun Lin, Yu-Lun Huang, Chi-Yen Huang, and Shankar Sastry. 2011. Attacks Against Process Control Systems: Risk Assessment, Detection, and Response. In Proceedings of the 6th ACM Symposium on Information, Computer and Communications Security. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  9. Alvaro Cárdenas, Saurabh Amin, Bruno Sinopoli, Annarita Giani, Adrian Perrig, and Shankar Sastry. 2009. Challenges for Securing Cyber Physical Systems. In Workshop on Future Directions in Cyber-Physical Systems Security.Google ScholarGoogle Scholar
  10. Thomas Chen and Saeed Abu-Nimeh. 2011. Lessons from Stuxnet. Computer (2011). Google ScholarGoogle ScholarDigital LibraryDigital Library
  11. Steven Cheung, Bruno Dutertre, Martin Fong, Ulf Lindqvist, Keith Skinner, and Alfonso Valdes. 2007. Using Model-Based Intrusion Detection for SCADA Networks Proceedings of the SCADA security scientific symposium. Citeseer.Google ScholarGoogle Scholar
  12. James Downs and Ernest Vogel. 1993. A Plant-Wide Industrial Process Control Problem. Computers & Chemical Engineering (1993).Google ScholarGoogle Scholar
  13. James B Elsner and Anastasios A Tsonis. 2013. Singular Spectrum Analysis: A New Tool in Time Series Analysis. Springer Science & Business Media.Google ScholarGoogle Scholar
  14. Nicolas Falliere, Liam Murchu, and Eric Chien. 2011. W32. Stuxnet Dossier. White paper, Symantec Corp., Security Response (2011).Google ScholarGoogle Scholar
  15. Cheng Feng, Tingting Li, and Deeph Chana. 2017. Multi-Level Anomaly Detection in Industrial Control Systems via Package Signatures and LS™ Networks 47th Annual IEEE/IFIP International Conference on Dependable Systems and Networks (DSN). IEEE.Google ScholarGoogle Scholar
  16. Jonathan Goh, Sridhar Adepu, Khurum Nazir Junejo, and Aditya Mathur. 2016. A Dataset to Support Research in the Design of Secure Water Treatment Systems International Conference on Critical Information Infrastructures Security. Springer.Google ScholarGoogle Scholar
  17. Nina Golyandina and Anton Korobeynikov. 2014. Basic Singular Spectrum Analysis and Forecasting with R. Computational Statistics & Data Analysis (2014).Google ScholarGoogle Scholar
  18. Nina Golyandina, Vladimir Viktorovich Nekrutkin, and Anatoly Alexandrovich Zhigljavsky. 2001. Analysis of Time Series Structure: SSA and Related Techniques. Chapman & Hall/CRC.Google ScholarGoogle Scholar
  19. Nina Golyandina and Anatoly Zhigljavsky. 2013. Singular Spectrum Analysis for Time Series. Springer Science & Business Media.Google ScholarGoogle Scholar
  20. Naman Govil, Anand Agrawal, and Nils Ole Tippenhauer. 2017. On Ladder Logic Bombs in Industrial Control Systems. In Computer Security. Springer.Google ScholarGoogle Scholar
  21. Bengt Gregory-Brown. 2017. Securing Industrial Control Systems-2017. SANS Institute InfoSec Reading Room (2017).Google ScholarGoogle Scholar
  22. Dina Hadvziosmanović, Robin Sommer, Emmanuele Zambon, and Pieter H Hartel. 2014. Through the Eye of the PLC: Semantic Security Monitoring for Industrial Processes. In Proceedings of the 30th Annual Computer Security Applications Conference. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  23. Hossein Hassani. 2010. A Brief Introduction to Singular Spectrum Analysis. Optimal Decisions in Statistics and Data Analysis (2010).Google ScholarGoogle Scholar
  24. John Hearon. 1967. Partially Isometric Matrices. J. Res. Nat. Bur. Standards Sect. B (1967).Google ScholarGoogle Scholar
  25. Blake Johnson, Dan Caban, Marina Krotofil, Dan Scali, Nathan Brubaker, and Christopher Glyer. 2017. Attackers Deploy New ICS Attack Framework “TRITON” and Cause Operational Disruption to Critical Infrastructure. https://www.fireeye.com/blog/threat-research/2017/12/attackers-deploy-new-ics-attack-framework-triton.html. Last visited 2018-08-01.Google ScholarGoogle Scholar
  26. Khurum Nazir Junejo and Jonathan Goh. 2016. Behaviour-Based Attack Detection and Classification in Cyber Physical Systems Using Machine Learning. In Proceedings of the 2nd ACM International Workshop on Cyber-Physical System Security. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  27. Andrew Kerns, Daniel Shepard, Jahshan Bhatti, and Todd Humphreys. 2014. Unmanned Aircraft Capture and Control via GPS Spoofing. Journal of Field Robotics (2014). Google ScholarGoogle ScholarDigital LibraryDigital Library
  28. Istvan Kiss, Bela Genge, and Piroska Haller. 2015. A Clustering-Based Approach to Detect Cyber Attacks in Process Control Systems Industrial Informatics (INDIN).Google ScholarGoogle Scholar
  29. Marina Krotofil and Alvaro Cárdenas. 2013. Resilience of Process Control Systems to Cyber-Physical Attacks Nordic Conference on Secure IT Systems. Springer. Google ScholarGoogle ScholarDigital LibraryDigital Library
  30. Marina Krotofil and Jason Larsen. 2015. Rocking the Pocket Book: Hacking Chemical Plants DefCon Conference, DEFCON.Google ScholarGoogle Scholar
  31. Marina Krotofil, Jason Larson, and Dieter Gollmann. 2015. The Process Matters: Ensuring Data Veracity in Cyber-Physical Systems Proceedings of the 10th ACM Symposium on Information, Computer and Communications Security (ASIA CCS '15). ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  32. Truls Larsson, Kristin Hestetun, Espen Hovland, and Sigurd Skogestad. 2001. Self-Optimizing Control of a Large-Scale Plant: The Tennessee Eastman Process. Industrial & Engineering Chemistry Research (2001).Google ScholarGoogle Scholar
  33. Robert Lee, Michael Assante, and Tim Conway. 2014. German Steel Mill Cyber Attack. Technical Report. SANS Industrial Control Systems.Google ScholarGoogle Scholar
  34. Robert Lee, Michael Assante, and Tim Conway. 2016. Analysis of the Cyber Attack on the Ukrainian Power Grid. Technical Report. SANS Industrial Control Systems and E-ISAC.Google ScholarGoogle Scholar
  35. Yao Liu, Peng Ning, and Michael Reiter. 2011. False Data Injection Attacks Against State Estimation in Electric Power Grids. ACM Transactions on Information and System Security (TISSEC) (2011). Google ScholarGoogle ScholarDigital LibraryDigital Library
  36. Aditya Mathur and Nils Tippenhauer. 2016. SWaT: A Water Treatment Testbed for Research and Training on ICS Security 2016 International Workshop on Cyber-physical Systems for Smart Water Networks (CySWater).Google ScholarGoogle Scholar
  37. Thomas McEvoy and Stephen Wolthusen. 2011. A Plant-Wide Industrial Process Control Security Problem International Conference on Critical Infrastructure Protection. Springer.Google ScholarGoogle Scholar
  38. Yilin Mo and Bruno Sinopoli. 2016. On the Performance Degradation of Cyber-Physical Systems under Stealthy Integrity Attacks. IEEE Trans. Automat. Control (2016).Google ScholarGoogle ScholarCross RefCross Ref
  39. Valentina Moskvina and Anatoly Zhigljavsky. 2003. An Algorithm Based on Singular Spectrum Analysis for Change-Point Detection. Communications in Statistics-Simulation and Computation (2003).Google ScholarGoogle Scholar
  40. Patric Nader, Paul Honeine, and Pierre Beauseroy. 2014. Lp-Norms in One-Class Classification for Intrusion Detection in SCADA Systems. IEEE Transactions on Industrial Informatics (2014).Google ScholarGoogle Scholar
  41. Nell Nelson. 2016. The Impact of Dragonfly Malware on Industrial Control Systems. SANS Institute (2016).Google ScholarGoogle Scholar
  42. Shengyi Pan, Thomas Morris, and Uttam Adhikari. 2015. Developing a Hybrid Intrusion Detection System Using Data Mining for Power Systems. IEEE Transactions on Smart Grid (2015).Google ScholarGoogle ScholarCross RefCross Ref
  43. Vern Paxson. 1999. Bro: A System for Detecting Network Intruders in Real-Time. Computer networks (1999). Google ScholarGoogle ScholarDigital LibraryDigital Library
  44. Pavel Polityuk, Oleg Vukmanovic, and Stephen Jewkes. 2017. Ukraine's Power Outage was a Cyber Attack: Ukrenergo. https://www.reuters.com/article/us-ukraine-cyber-attack-energy/ukraines-power-outage-was-a-cyber-attack-ukrenergo-idUSKBN1521BA. Last visited 2018-08-01.Google ScholarGoogle Scholar
  45. Lawrence Ricker. 1996. Decentralized Control of the Tennessee Eastman Challenge Process. Journal of Process Control (1996).Google ScholarGoogle Scholar
  46. Yasser Shoukry, Paul Martin, Yair Yona, Suhas Diggavi, and Mani Srivastava. 2015. PyCRA: Physical Challenge-Response Authentication for Active Sensors under Spoofing Attacks. In Proceedings of the 22nd ACM SIGSAC Conference on Computer and Communications Security. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  47. Ralf Spenneberg, Maik Brüggemann, and Hendrik Schwartke. 2016. PLC-Blaster: A Worm Living Solely in the PLC. Black Hat Asia, Marina Bay Sands, Singapore (2016).Google ScholarGoogle Scholar
  48. Keith Stouffer, Joe Falco, and Karen Scarfone. 2011. Guide to Industrial Control Systems (ICS) Security. NIST special publication (2011).Google ScholarGoogle Scholar
  49. Gilbert Strang. 2016. Introduction to Linear Algebra. Wellesley-Cambridge Press.Google ScholarGoogle Scholar
  50. David Urbina, Jairo Giraldo, Alvaro Cárdenas, Nils Ole Tippenhauer, Junia Valente, Mustafa Faisal, Justin Ruths, Richard Candell, and Henrik Sandberg. 2016 a. Limiting the Impact of Stealthy Attacks on Industrial Control Systems Proceedings of the 2016 ACM SIGSAC Conference on Computer and Communications Security. ACM. Google ScholarGoogle ScholarDigital LibraryDigital Library
  51. David Urbina, Jairo Giraldo, Alvaro Cárdenas, Junia Valente, Mustafa Faisal, Nils Ole Tippenhauer, Justin Ruths, Richard Candell, and Henrik Sandberg. 2016 b. Survey and New Directions for Physics-Based Attack Detection in Control Systems. Technical Report. National Institute of Standards and Technology.Google ScholarGoogle Scholar
  52. Robert Vautard and Michael Ghil. 1989. Singular Spectrum Analysis in Nonlinear Dynamics, with Applications to Paleoclimatic Time Series. Physica D: Nonlinear Phenomena (1989).Google ScholarGoogle Scholar
  53. Oleg Vukmanovic and Stephen Jewkes. 2017. Suspected Russia-Backed Hackers Target Baltic Energy Networks. http://mobile.reuters.com/article/idUSKBN1871W5. Last visited 2018-08-01.Google ScholarGoogle Scholar
  54. Yu-jun Xiao, Wen-yuan Xu, Zhen-hua Jia, Zhuo-ran Ma, and Dong-lian Qi. 2017. NIPAD: A Non-Invasive Power-Based Anomaly Detection Scheme for Programmable Logic Controllers. Frontiers of Information Technology & Electronic Engineering (2017).Google ScholarGoogle Scholar

Index Terms

  1. Truth Will Out: Departure-Based Process-Level Detection of Stealthy Attacks on Control Systems

    Comments

    Login options

    Check if you have access through your login credentials or your institution to get full access on this article.

    Sign in

    PDF Format

    View or Download as a PDF file.

    PDF

    eReader

    View online with eReader.

    eReader
    About Cookies On This Site

    We use cookies to ensure that we give you the best experience on our website.

    Learn more

    Got it!