conference-paper

Digital Forensics Process of an Attack Vector in ICS environment

  • 2021 IEEE International Conference on Big Data (Big Data)
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Abstract

Industrial control systems (ICS) can be exposed to cyberattacks with potentially catastrophic consequences. Intrusion detection is a fraud prevention technique derived from big data that play a key role in detecting attacks at the earliest stage. Data historian is essential to understanding all events and activities across the network. This article introduces the basic mechanisms by which common attacks on ICS can be detected and analyzed through different forensic tools. We explored the common vulnerabilities and potential attack vectors present in critical infrastructures and described measures that can be deployed to mitigate those threats. We discussed several common attack scenarios and artifacts that a forensic analysis of an affected ICS device can recover to help diagnose an attack. An ICS test lab was implemented and used to examine the common attacks. A menu driven set of forensic tools specific for ICS was developed to allow the extraction and analysis of the resulting attack vector.

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Publication details

DOI
10.1109/bigdata52589.2021.9671986
OpenAlex
W4205197557
Document type
conference-paper
Language
EN
Source
2021 IEEE International Conference on Big Data (Big Data)
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