Analysis of location spoofing identification in cellular networks

Yuxin Wei, Dawei Liu*

*Corresponding author for this work

Research output: Chapter in Book or Report/Conference proceedingConference Proceedingpeer-review

1 Citation (Scopus)

Abstract

Location spoofing is considered as a serious threat to positioning and location based services in wireless networks. Existing identification methods for location spoofing have focused primarily on wireless sensor networks. These methods may not be applicable in cellular networks due to the following two limitations: (i) relying on accurate distance measurement; (ii) incapable of dealing with bad propagation conditions. To address these two issues, we carry out an analysis of location spoofing based on angle-of-arrival (AOA) and time-difference-of-arrival (TDOA) measurement models, two commonly used signal measurement models in cellular networks, in bad propagation conditions with large measurement errors. Our analysis shows that AOA model is more robust to location spoofing in noisy conditions.

Original languageEnglish
Title of host publicationMobile, Secure, and Programmable Networking - 1st International Conference, MSPN 2015, Selected Papers
EditorsSelma Boumerdassi, Samia Bouzefrane, Éric Renault
PublisherSpringer Verlag
Pages18-27
Number of pages10
ISBN (Print)9783319257433
DOIs
Publication statusPublished - 2015
Event1st International Conference on Mobile, Secure, and Programmable Networking, MSPN 2015 - Paris, France
Duration: 15 Jun 201517 Jun 2015

Publication series

NameLecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume9395
ISSN (Print)0302-9743
ISSN (Electronic)1611-3349

Conference

Conference1st International Conference on Mobile, Secure, and Programmable Networking, MSPN 2015
Country/TerritoryFrance
CityParis
Period15/06/1517/06/15

Fingerprint

Dive into the research topics of 'Analysis of location spoofing identification in cellular networks'. Together they form a unique fingerprint.

Cite this