Detecting IMSI-Catcher Using Soft Computing

  • Thanh van DoEmail author
  • Hai Thanh Nguyen
  • Nikolov Momchil
  • Van Thuan Do
Conference paper
Part of the Communications in Computer and Information Science book series (CCIS, volume 545)


Lately, from a secure system providing adequate user’s protection of confidentiality and privacy, the mobile communication has been degraded to be a less trustful one due to the revelation of IMSI catchers that enable mobile phone tapping. To fight against these illegal infringements there are a lot of activities aiming at detecting these IMSI catchers. However, so far the existing solutions are only device-based and intended for the users in their self-protection. This paper presents an innovative network-based IMSI catcher solution that makes use of machine learning techniques. After giving a brief description of the IMSI catcher the paper identifies the attributes of the IMSI catcher anomaly. The challenges that the proposed system has to surmount are also explained. Last but least, the overall architecture of the proposed Machine Learning based IMSI catcher Detection system is described thoroughly.


IMSI catcher detection mobile phone tapping phone eavesdropping machine learning anomaly detection 


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Copyright information

© Springer Science+Business Media Singapore 2015

Authors and Affiliations

  • Thanh van Do
    • 1
    • 2
    Email author
  • Hai Thanh Nguyen
    • 1
  • Nikolov Momchil
    • 1
  • Van Thuan Do
    • 3
  1. 1.Telenor ASA.FornebuNorway
  2. 2.Norwegian University of Science and TechnologyTrondheimNorway
  3. 3.Linus ASFornebuNorway

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