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KTH, School of Electrical Engineering (EES), Industrial Information and Control Systems.
2011 (English)Independent thesis Advanced level (degree of Master (Two Years)), 20 credits / 30 HE creditsStudent thesisAlternative title
Incidenthantering : Återställningstider För SCADA och Administrativa IT-system (Swedish)
Abstract [en]

For virtually any company today regardless of scale, IT is a necessity. By supporting the core business, the productivity can be greatly enhanced. This of course being an important asset is also a potential threat. As business processes rely heavily on IT, new possibilities open up for ill-minded people to cause damage to the company. This thesis aims at estimating the time it takes to fully restore a system struck by an incident, whether it is a SCADA or an administrative IT system. The factors that contribute to the restoration assessments are important and in focus as well. The greatest limitation is the abstraction level of the factors that contribute to the restoration time, i.e. low-level technical details such as RPM on the hard drive or latency of the RAM are out of scope. The overarching methodology utilizes Bayesian networks to manage the contribution factors, quantitative data and end result estimations. To keep the results short; the SCADA systems have a restoration time of 43 hours and the administrative systems lie at 0 hours. The full magnitude of the results can be used to retrieve a semi-precise estimation given a scenario determined by a configuration of the contributing factors. Furthermore, the report identifies the most important factors that contribute the most, to the reduction of restoration times. The named factors should be the ones in focus when attempting to further reduce the impact of an incident in terms of restoration time.

Place, publisher, year, edition, pages
EES Examensarbete / Master Thesis
Keyword [en]
Information Security. Incident Management. Incident handling. SCADA. BIT. Restoration Time. Master Thesis. Incident. Incident Framework. General Incident Process Model
National Category
Electrical Engineering, Electronic Engineering, Information Engineering
URN: urn:nbn:se:kth:diva-81450OAI: diva2:497474
Educational program
Master of Science in Engineering - Computer Science and Technology
Available from: 2012-02-28 Created: 2012-02-10 Last updated: 2012-03-02Bibliographically approved

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Lindgren, Linus
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