Device Identification from Network Traffic Measurements - A HTTP User Agent Based Method

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dc.contributor Aalto-yliopisto fi
dc.contributor Aalto University en
dc.contributor.advisor Riikonen, Antti
dc.contributor.author Adhikari, Aashish
dc.date.accessioned 2012-11-23T06:36:25Z
dc.date.available 2012-11-23T06:36:25Z
dc.date.issued 2012
dc.identifier.uri https://aaltodoc.aalto.fi/handle/123456789/6101
dc.description.abstract The proliferation of mobile Internet in recent years has created an increasing need to understand the usage of the mobile services. With widespread adoption of the Internet capable mobile handheld devices, knowledge about mobile Internet usage is beneficial from different aspects of the stakeholders. A key challenge is that the factual information available on User Agent (UA) based device identification from IP traffic measurements is limited. The objective of our research is two folded; to develop a tool to identify mobile devices based on the HTTP UA obtained from the network traffic measurements and to profile mobile Internet usage in Finland. We observe that the tool can be developed by using a device description repository (DDR) and its API to interact with the repository and extract device related information. Moreover, the results from the DDR implementation can be improved by enhancing its original output. With the identification results, we provide descriptive statistics to aid in profiling the usage of the mobile Internet in Finnish mobile networks. Wireless Universal Resource File (WURFL) DDR based tool produced accurate identification of the devices from the HTTP UA strings. However, identification of the devices from the UA strings generated by the applications other than the web browsers required additional programming. The resulting enhanced WURFL tool was able to improve the device identification results roughly by 15% points with our dataset. Based on the assessment of the enhanced WURFL tool, we observe that roughly 94% of the total UA strings subjected to the analysis were identified correctly. The share of incorrectly identified UA strings was about 0.5%. The data analysis results indicate that the majority of mobile handset traffic is generated by handsets with advanced capabilities such as 3G and the touchscreen, manufactured by numerous brands of mobile devices with different operating systems. The results from the identification of these devices and device features could be utilized by the operators to support the pricing and business development. en
dc.format.extent [6] + 72 s.
dc.format.mimetype application/pdf
dc.language.iso en en
dc.title Device Identification from Network Traffic Measurements - A HTTP User Agent Based Method en
dc.type G2 Pro gradu, diplomityö fi
dc.contributor.school Sähkötekniikan korkeakoulu fi
dc.contributor.department Tietoliikenne- ja tietoverkkotekniikan laitos fi
dc.subject.keyword network traffic measurements en
dc.subject.keyword mobile internet en
dc.subject.keyword device identification en
dc.subject.keyword HTTP user agent en
dc.subject.keyword DDR en
dc.subject.keyword WURFL en
dc.subject.keyword Java API en
dc.identifier.urn URN:NBN:fi:aalto-201211243396
dc.type.dcmitype text en
dc.programme.major Tietoverkkotekniikka fi
dc.programme.mcode S-38
dc.type.ontasot Diplomityö fi
dc.type.ontasot Master's thesis en
dc.contributor.supervisor Hämmäinen, Heikki
dc.location P1 fi


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