A Mobile Offloading Game Against Smart Attacks

Liang Xiao, Caixia Xie, Tianhua Chen, Huaiyu Dai, H. Vincent Poor

Research output: Contribution to journalArticle

46 Scopus citations

Abstract

Mobile devices, such as smartphones, can offload applications and data to the cloud via access points or base stations to reduce energy consumption and improve user experience. However, mobile offloading is vulnerable to smart attackers that use smart and programmable radio devices, such as universal software radio peripherals, to perform multiple types of attacks, such as spoofing and jamming, based on the radio environment and offloading transmissions. In this paper, a mobile offloading game is investigated that consists of three players: a mobile device that chooses its offloading rate, a smart attacker that determines its attack mode, and a security agent that decides whether or not to initiate full protection for the serving access point during the offloading. Nash and Stackelberg equilibria of the offloading game are derived and their existence conditions are discussed. A Q-learning-based mobile offloading strategy is proposed for mobile devices that are unaware of system parameters, such as the channel conditions, in dynamic radio environments. Simulation results show that the proposed offloading strategy can improve the utility of the mobile device and reduce the attack rate of smart attackers.

Original languageEnglish (US)
Article number7466787
Pages (from-to)2281-2291
Number of pages11
JournalIEEE Access
Volume4
DOIs
StatePublished - Jan 1 2016

All Science Journal Classification (ASJC) codes

  • Computer Science(all)
  • Materials Science(all)
  • Engineering(all)

Keywords

  • Mobile offloading
  • Q-learning
  • game theory
  • jamming
  • smart attacks
  • spoofing

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