Purpose – The purpose of this study is partly to illustrate how the AES encryption methods ECB and CTR affect the computational speed when using the GPGPU framework Cuda, but also to clarify the advantages and disadvantages between the different AES encryption modes. Method – A preliminary study was conducted to obtain empirical data on the AES encryption modes ECB and CTR. Data from the study has been analyzed and compared to determine the various aspects of the AES encryption modes and to create a basis for determining the advantages and disadvantages between them. The preliminary study has been carried out systematically by finding scientific works by searching databases within the subject. An experiment has been used as a method to be able to extract execution time data for the GPGPU framework Cuda when processing the AES encryption modes. Experiment were chosen as a method to gain control over the variables included in the study and to see how these variables change when they are consciously influenced. Findings – The findings of the preliminary study show that CTR is more secure than the ECB, but also considerably more complex, which can lead to integrity risks when implementation is done incorrectly. In the experiment, computational speeds are produced when the CPU memory sends to the GPU memory, the encryption on the GPU and how long it takes for the GPU memory to send to the CPU memory. This is done for both CTR and ECB in encryption and decryption. The result of the analysis shows that the ECB is faster than CTR in encryption and decryption. The calculation speed is higher with the ECB compared to the CTR. Implications – The experiment shows that CTR is slower than the ECB. But the most amount of time spent in encryption for both modes are the transfers between the CPU memory and the GPU memory. Limitations – The file sizes of the files tested only goes up to about 1 gigabyte which gave small computation times.
Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:hj-50809 |
Date | January 2020 |
Creators | Vidén, Pontus, Henningsson, Viktor |
Publisher | Tekniska Högskolan, Jönköping University, JTH, Datateknik och informatik, Tekniska Högskolan, Jönköping University, JTH, Datateknik och informatik |
Source Sets | DiVA Archive at Upsalla University |
Language | Swedish |
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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