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DC Field | Value | Language |
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dc.contributor.advisor | Mekala, Priyanka | |
dc.contributor.advisor | Goel, Supriya | |
dc.contributor.author | Panda, Nrusingha Prasad | |
dc.date.accessioned | 2022-05-06T06:57:51Z | |
dc.date.available | 2023-02-25T06:57:51Z | |
dc.date.issued | 2021 | |
dc.identifier.citation | Panda, Nrusingha Prasad (2021). Enhanced Device FingerPrinting in 4G LTE Communication Networks. Dhirubhai Ambani Institute of Information and Communication Technology. vii, 57 p. (Acc.No: T00995) | |
dc.identifier.uri | http://drsr.daiict.ac.in//handle/123456789/1055 | |
dc.description.abstract | Long Term Evolution in the field of mobile wireless communication, its wide availability and the surge of data usage among the millennial in recent years, which led to the new world of information society, plays the pivotal role in our technology driven daily life which demands high performance data transmission, sophisticated security features and extensive integration. Having to serve Billions of 4G users worldwide, LTE network architecture compliments the aspect of user privacy and data security along with connectivity, speed, latency, throughput etc compared to its previous generations. We want to review the LTE architecture, OSI layers and protocols, specifically focusing on the layer 3. In the layer 3 which is the network layer we can investigate the impact of fingerprinting on encrypted LTE/4G Control Plane traffic and exploiting the vulnerabilities by analysing the control signals. Then auditing different features may lead to extraction of useful information, and classifying them based on our classification model. Also a GUI is designed and a fuzzy inference system is outlined to categorise the threat factor for the individual UEs using the model. | |
dc.subject | 4G LTE | |
dc.subject | FingerPrinting | |
dc.subject | Device Capability | |
dc.subject | Attach Procedure | |
dc.subject | LTE Protocols | |
dc.classification.ddc | 005.82 PAN | |
dc.title | Enhanced Device FingerPrinting in 4G LTE Communication Networks | |
dc.type | Dissertation | |
dc.degree | M. Tech (EC) | |
dc.student.id | 201915006 | |
dc.accession.number | T00995 | |
Appears in Collections: | M Tech (EC) Dissertations |
Files in This Item:
File | Description | Size | Format | |
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Thesis_report_201915006_signed_supriya_priyanka.pdf | 3.48 MB | Adobe PDF | View/Open |
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