The ubiquity and speed of Internet access led over the past decade to an exponential increase in the use of thin clients and cloud computing, both taking advantage of the ability to remotely provide computing resources. The work investigates the role of remote display Protocol in behavioral biometric systems based on free-text keystroke dynamics. Authentication based on keystroke dynamics is easy in use, cheap, invisible for user and does not require any additional sensor.I n this project I will investigate how network characteristics affect the keystroke dynamics pattern in remote desktop scenario. Objectives: The aim of this project is to investigate the role of remote display Protocol in behavioral biometric system based on free-text keystroke dynamics, by measuring how network characteristics influence the computation of keystroke pattern in Virtual Desktop Infrastructure (VDI). Method: This thesis will answer all of its research question with the help of a Systematic Literature Review (SLR) and an Experiment. Literature review was conducted to gather information about the keystroke dynamics analysis, the applied algorithms and their performance; and to clarify the controlled changes of networking performance in VDI based scenario. Using the acquired knowledge, implemented keystroke dynamics pattern algorithm based on Euclidian distance statistical method, designed an experiment and performed a series of tests, in order to identify the influence of remote display protocol to keystroke pattern. Results: Through the SLR, keystroke dynamics analysis working structure is identified and illustrated, essential elements are summarized, and a statistical approach based on Euclidian distance is described; a technique to simulate and measure networklatency in VDI scenario is described including essential elements and parameters of VDI testbed. Keystroke analysis algorithm, dataset replication code and VDItestbed are implemented. The controlled experiment provided measurements of the metrics of the algorithm and network performance mentioned in objectives. Conclusions: During experimentation, I found that timing pattern in the keystroke dynamics data is affected by VDI in normal network conditions by 12% in average. Higher latency standard deviation, jitter, packet loss as well as remote display protocol overheads have a significant combined impact onto keystroke pattern. Moreover I found what maximum possible delay values does not affect keystroke pattern in a larger extent.
| Identifer | oai:union.ndltd.org:UPSALLA1/oai:DiVA.org:bth-20124 |
| Date | January 2020 |
| Creators | Silonosov, Alexandr |
| Publisher | Blekinge Tekniska Högskola, Institutionen för datavetenskap |
| 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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