Adaptive Misbehavior Detection in IEEE 802.11TM Based on Markov Decision Process

  • Jin Tang
  • Yu Cheng
Part of the SpringerBriefs in Computer Science book series (BRIEFSCOMPUTER)


To achieve better detection performance, we enhance the FS detector from Chap. 2 to develop an adaptive detector with the Markov decision process (MDP). In particular, we adaptively make decisions on how aggressively the detector value should be updated in each step. Then based on a reward function defined by us, we are able to determine an optimal decision policy to maximize the overall system benefit through a linear programming formulation. The optimal policy also indicates the operation of the adaptive detector, which yields better performance in both false positive rate and detection delay. Both theoretical analysis and simulation results are provided to demonstrate the performance of the adaptive detector.


Optimal Policy Markov Decision Process Malicious Node Successful Transmission Reward Function 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.


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Copyright information

© The Author(s) 2013

Authors and Affiliations

  • Jin Tang
    • 1
  • Yu Cheng
    • 2
  1. 1.AT&T LabsWarrenvilleUSA
  2. 2.Department of Electrical and Computer EngineeringIllinois Institute of TechnologyChicagoUSA

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