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To Implement  Real-Time Detection of Selfish Behavior in IEEE 802.11 Wireless Networks Ravi Kiran Paladugu Future Networki...
Outline <ul><li>Objective </li></ul><ul><li>Test-bed – “successfully Implemented” </li></ul><ul><li>Detector – “static imp...
Background <ul><li>With high growing rate of IEEE 802.11 based wireless networks in recent years the security became a con...
Contd… <ul><li>The open and distributed nature of the protocol makes it possible for selfish nodes to deliberately modify ...
Objective: <ul><li>With the above focused disadvantages we are motivated to develop a real-time detection scheme and to id...
Detection Scheme <ul><li>The two challenges are to detect  unknown selfish behavior strategy  and  real-time detection. </...
Contd.. <ul><li>We now monitor the number of successful transmissions of the tagged node every T successful transmissions ...
Demo:
Future Work: <ul><li>To be able to detect strategy and to implement dynamic detector </li></ul>
Reference : <ul><li>Real-Time Detection of Selfish Behavior in IEEE 802.11 Wireless Networks </li></ul><ul><ul><li>(Jin Ta...
 
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CPS Final Presentation

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CPS Final Presentation

  1. 1. To Implement Real-Time Detection of Selfish Behavior in IEEE 802.11 Wireless Networks Ravi Kiran Paladugu Future Networking Laboratory (FuNLabs)
  2. 2. Outline <ul><li>Objective </li></ul><ul><li>Test-bed – “successfully Implemented” </li></ul><ul><li>Detector – “static implementation achieved” </li></ul><ul><li>Video Demo </li></ul><ul><li>Future work </li></ul><ul><li>Conclusion </li></ul>
  3. 3. Background <ul><li>With high growing rate of IEEE 802.11 based wireless networks in recent years the security became a concern </li></ul><ul><li>As a contention based protocol, 802.11 assumes that every participant in the network acts in compliance with the protocol rules </li></ul>
  4. 4. Contd… <ul><li>The open and distributed nature of the protocol makes it possible for selfish nodes to deliberately modify the protocol parameters </li></ul><ul><li>This leads to unfair share to the network at the expenses of other normal node’s channel access </li></ul>
  5. 5. Objective: <ul><li>With the above focused disadvantages we are motivated to develop a real-time detection scheme and to identify the malicious node </li></ul><ul><li>We also want to detect the unknown selfish behavior strategy </li></ul><ul><li>Also I would like to track the successful transmissions and have log of it for dynamic expansion and contraction of the congestion window </li></ul>
  6. 6. Detection Scheme <ul><li>The two challenges are to detect unknown selfish behavior strategy and real-time detection. </li></ul><ul><li>We came up with an detection scheme based on non-parametric cumulative sum (CUSUM) test </li></ul><ul><li>The CUSUM test statistic is able to accumulate the deviation brought by the selfish behavior of a malicious node and raise an alarm </li></ul>
  7. 7. Contd.. <ul><li>We now monitor the number of successful transmissions of the tagged node every T successful transmissions of the whole network </li></ul><ul><li>As a selfish node is likely to always obtain more opportunities, the cumulative effect of its selfish behavior can quickly be captured by the CUSUM test </li></ul><ul><li>Once the CUSUM detects it, an alarm is then raised </li></ul>
  8. 8. Demo:
  9. 9. Future Work: <ul><li>To be able to detect strategy and to implement dynamic detector </li></ul>
  10. 10. Reference : <ul><li>Real-Time Detection of Selfish Behavior in IEEE 802.11 Wireless Networks </li></ul><ul><ul><li>(Jin Tang, Yu Cheng, Yong Hao and Chi Zhou; Dept. of Electrical Engineering, Illinois Institute of Technology) </li></ul></ul><ul><li>An analytical approach to real-time misbehavior detection in IEEE 802.11 based wireless networks </li></ul><ul><ul><li>(Jin Tang, Yu Cheng and W. Zhuang, Proc. IEEE INFOCOM, Shanghai, China, Apr 10-15, 2011.) </li></ul></ul>

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