This master thesis report presents the development process and result of an artificial neural network model that can predict if a file has been encrypted. It was developed as a stand alone component that can be implemented in to a backup system. The development process was tested to determine the best possible outcome and it was implemented to a rudimentary backup system. The resulting software was a command line interface that gave the user full access to the training and testing process. The backup system is also implemented in this command line interface for test purposes. The model was successful in identifying encrypted files.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:liu-170251 |
| Date | January 2020 |
| Creators | Eriksson, David |
| Publisher | Linköpings universitet, Medie- och Informationsteknik, Linköpings universitet, Tekniska högskolan |
| Source Sets | DiVA Archive at Upsalla University |
| Language | English |
| Detected Language | English |
| Type | Student thesis, info:eu-repo/semantics/bachelorThesis, text |
| Format | application/pdf |
| Rights | info:eu-repo/semantics/openAccess |
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