IMSI Catcher Detection Method for Cellular Networks

Alrashede, Hamad and Shaikh, Riaz Ahmed (2019) IMSI Catcher Detection Method for Cellular Networks. In: 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019. 2nd International Conference on Computer Applications and Information Security, ICCAIS 2019 . Institute of Electrical and Electronics Engineers Inc., SAU. ISBN 9781728101088

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Abstract

Mobile communications are not trustful as many people think about it. The IMSI catcher device is one of the most effective threats that can compromise the security of mobile communications. It is a radio device that acts as a fake cellular base station allowing near mobiles to join it instead of legitimate base stations. It uses a type of attack called man in the middle (MITM). The IMSI catcher can do almost everything after being connected to its victims, such as eavesdropping calls, intercepting SMS messages, locating phone's location and so many. It is widely used by government agencies legally to track criminals and terrorists, but nowadays it could be used by unauthorized individuals and criminal organizations for different purposes. Several of countermeasures against this threat are proposed by many researchers but most of them are reliant on real base station features to expose fake base stations. Those features are limited and could be easily imitated by IMSI catcher device. This paper presents a new IMSI catcher detection method, which relies on location area features for detection that makes it unique as compared to most of the existing schemes.

Item Type: Book Section
Additional Information: Publisher Copyright: © 2019 IEEE.
Uncontrolled Keywords: cell site simulator,fake base station,imsi catcher,mobile network security,mobile privacy,computer networks and communications,computer science applications,information systems and management,health informatics,information systems,safety, risk, reliability and quality,artificial intelligence,sdg 16 - peace, justice and strong institutions ,/dk/atira/pure/subjectarea/asjc/1700/1705
Faculty \ School: Faculty of Science > School of Computing Sciences
Related URLs:
Depositing User: LivePure Connector
Date Deposited: 16 Aug 2022 15:30
Last Modified: 24 Sep 2022 08:32
URI: https://ueaeprints.uea.ac.uk/id/eprint/87297
DOI: 10.1109/CAIS.2019.8769507

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