Academia.eduAcademia.edu

Outline

Forensics in Industrial Control System: A Case Study

2016, Lecture Notes in Computer Science

https://doi.org/10.1007/978-3-319-40385-4_10

Abstract

Industrial Control Systems (ICS) are used worldwide in critical infrastructures. An ICS system can be a single embedded system working standalone for controlling a simple process or ICS can also be a very complex Distributed Control System (DCS) connected to Supervisory Control And Data Acquisition (SCADA) system(s) in a nuclear power plant. Although ICS are widely used today, there are very little research on the forensic acquisition and analyze ICS's artefacts. In this paper we present a case study of forensics in ICS where we describe a method of safeguarding important volatile artefacts from an embedded industrial control system and several other sources.

References (15)

  1. T. Wu et al, Towards a SCADA Forensics Architecture, Newport, 2013.
  2. R. Barbosa, Anomaly Detection in SCADA Systems, Enschede, 2014
  3. R.van der Knijff, Control systems/SCADA forensics, what's the difference, The Hague, 2014.
  4. U.S. Department of Homeland Security, Creating Cyber Forensics Plans for Control Sys- tems, Idaho, 2008
  5. Boyer, Stuart, SCADA Supervisory Control and Data Acquisition, 2nd Edition, ISA, 1999
  6. Modbus, http://en.wikipedia.org/wiki/Modbus [accessed on 4-2-2015]
  7. Profibus, http://en.wikipedia.org/wiki/Profibus [accessed on 4-2-2015].
  8. 9. CRISALIS, Critical Infrastructure Security Analysis http://www.crisalis-project.eu/, 2015
  9. Security Onion Linux suite, http://www.securityonion.net [accessed 17-5-2015]
  10. Wireshark, https://wiki.wireshark.org/CaptureSetup/Ethernet
  11. E. Hjelmvik, SCADA Network Forensics, Stockholm, 2014
  12. L. M. Aouad, N-A. Le-Khac and M-T. Kechadi, "Lightweight Clustering Technique for Distributed Data Mining Applications", 7th Industrial Conference on Data Mining Spring- er LNAI 4597, July 14-18, 2007, Leipzig, Germany.
  13. N-A. Le-Khac, L.M. Aouad and M-T. Kechadi, "A New Approach for Distributed Density Based Clustering on Grid Platform", Chapter in Data Management, Data, Data Every- where, Lecture Notes in Computer Science, pp. 247-258, 24th British National Conference on Databases, BNCOD 24, Glasgow, UK, July 3-5, 2007.
  14. N-A. Le-Khac, L.M. Aouad and M-T. Kechadi, "Distributed Knowledge Map for Mining Data on Grid Platforms", IJCSNS International Journal of Computer Science and Network 98
  15. Security, Vol.7, No.10, October 2007.