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Uncovering the footprints of malicious traffic in cellular data networks

  • Author(s): Raghuramu, A
  • Zang, H
  • Chuah, CN
  • et al.
Abstract

© Springer International Publishing Switzerland 2015. In this paper, we present a comprehensive characterization of malicious traffic generated by mobile devices using Deep Packet Inspection (DPI) records and security event logs from a large US based cellular provider network. Our analysis reveals that 0.17% of mobile devices in the cellular network are affected by security threats. This proportion, while small, is orders of magnitude higher than the last reported (in 2013) infection rate of 0.0009%. We also perform a detailed comparison of infection rates of various mobile platforms and show that platforms deemed to be more secure by common opinion such as BlackBerry and iOS are not as safe as we think. However, Android still remains the most affected platform with an infection rate of 0.39%. We present a detailed discussion of the top threat families targeting mobile devices observed in our dataset. Lastly, we characterize the aggregate network footprint of malicious and benign traffic in the cellular network and show that statistical network features can be used to distinguish between these traffic classes.

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