Selfish manipulation of cooperative cellular communications via channel fabrication

  • Authors:

  • Shrikant Adhikarla;Min Suk Kang;Patrick Tague

  • Affiliations:

  • Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA;Carnegie Mellon University, Pittsburgh, PA, USA

  • Venue:
  • Proceedings of the sixth ACM conference on Security and privacy in wireless and mobile networks
  • Year:
  • 2013

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Abstract

In today's cellular networks, user equipment (UE) have suffered from low spectral efficiency at cell-edge region due to high interference from adjacent base stations (BSs), which share the same spectral radio resources. In the recently proposed cooperative cellular networks, geographically separated multiple BSs cooperate on transmission in order to improve the UE's signal-to-interference-plus-noise-ratio (SINR) at cell-edge region. The service provider of the system dynamically assigns the cluster of BSs to achieve higher SINR for the UE while optimizing the use of system radio resources. Although it is the service provider that makes the the clustering decision for the UE, the service provider relies on the UE's input to the decision; i.e., the channel states from the adjacent BSs to the UE. In essence, the operation of the cooperative cellular netwokrs heavily relies on the trust in the UEs. In this paper, we propose a new selfish attack against the cooperative cellular networks; an adversary reprograms her UE to report fabricated channel information to cause the service provider to make a decision that benefits the adversary while wasting its system resources. We evaluate the proposed attack in a cooperative cellular network having various performance goals on the simulation-based experiments and show that the adversary can trick the service provider into expending 3.7 times more radio resources for the adversary and, accordingly, the adversary achieves up to 16 dB SINR gain. Finally, we propose a threshold-based countermeasure for the service provider to detect the attack with approximately 90% of accuracy.