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Identification of Attack-based Digital Forensic Evidences for WAMPAC Systems
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
KTH, School of Electrical Engineering and Computer Science (EECS), Electrical Engineering, Electric Power and Energy Systems.ORCID iD: 0000-0003-3488-533X
Department of Information Security & Communication Technology, Norwegian University of Science and Technology, Norway.
KTH, School of Electrical Engineering and Computer Science (EECS), Computer Science, Network and Systems Engineering.
2018 (English)In: Proceedings - 2018 IEEE International Conference on Big Data, Big Data 2018, Seattle, Washington, USA: IEEE conference proceedings, 2018, p. 3078-3086, article id 8622550Conference paper, Published paper (Refereed)
Abstract [en]

Power systems domain has generally been very conservative in terms of conducting digital forensic investigations, especially so since the advent of smart grids. This lack of research due to a multitude of challenges has resulted in absence of knowledge base and resources to facilitate such an investigation. Digitalization in the form of smart grids is upon us but in case of cyber-attacks, attribution to such attacks is challenging and difficult if not impossible. In this research, we have identified digital forensic artifacts resulting from a cyber-attack on Wide Area Monitoring, Protection and Control (WAMPAC) systems, which will help an investigator attribute an attack using the identified evidences. The research also shows the usage of sandboxing for digital forensics along with hardware-in-the-loop (HIL) setup. This is first of its kind effort to identify and acquire all the digital forensic evidences for WAMPAC systems which will ultimately help in building a body of knowledge and taxonomy for power system forensics.

Place, publisher, year, edition, pages
Seattle, Washington, USA: IEEE conference proceedings, 2018. p. 3078-3086, article id 8622550
Keywords [en]
Forensic Investigations; Substation; Wide Area Monitoring Protection and Control; Forensic Artifacts; Evidence; PMUs.
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
Research subject
Electrical Engineering
Identifiers
URN: urn:nbn:se:kth:diva-240576DOI: 10.1109/BigData.2018.8622550ISI: 000468499303020Scopus ID: 2-s2.0-85062598217ISBN: 978-1-5386-5035-6 (electronic)OAI: oai:DiVA.org:kth-240576DiVA, id: diva2:1272780
Conference
2018 IEEE International Conference on Big Data, Big Data 2018; Seattle; United States; 10 December 2018 through 13 December 2018
Funder
Swedish Civil Contingencies Agency
Note

QC 20190108

Available from: 2018-12-19 Created: 2018-12-19 Last updated: 2024-03-15Bibliographically approved

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Iqbal, AsifMahmood, FarhanEkstedt, Mathias

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