Title :
Real-time misbehavior detection in IEEE 802.11e based WLANs
Author :
Xianghui Cao ; Lu Liu ; Wenlong Shen ; Jin Tang ; Yu Cheng
Author_Institution :
Dept. of Electr. & Comput. Eng., Illinois Inst. of Technol., Chicago, IL, USA
Abstract :
The Enhanced Distributed Channel Access (EDCA) specification in the IEEE 802.11e standard supports heterogeneous backoff parameters and arbitration inter-frame space (AIFS), which makes a selfish node easy to manipulate these parameters and misbehave. In this case, the network-wide fairness cannot be achieved any longer. Many existing misbehavior detectors, primarily designed for legacy IEEE 802.11 networks, become inapplicable in such a heterogeneous network configuration. In this paper, we propose a novel real-time hybrid-share (HS) misbehavior detector for IEEE 802.11e based wireless local area networks (WLANs). The detector keeps updating its state based on every successful transmission and makes detection decisions by comparing its state with a threshold. We develop mathematical analysis of the detector performance in terms of both false positive rate and average detection rate. Numerical results show that the proposed detector can effectively detect both contention window based and AIFS based misbehavior with only a short detection window.
Keywords :
wireless LAN; wireless channels; AIFS; EDCA; HS misbehavior detector; IEEE 802.11e based WLAN; arbitration interframe space; average detection rate; contention window detection; enhanced distributed channel access; heterogeneous network configuration; mathematical analysis; real-time hybrid share misbehavior detector; wireless local area network; Detectors; IEEE 802.11e Standard; Information systems; Real-time systems; Resource management; Wireless LAN; AIFS; IEEE 802.11e; contention window; detection rate; false positive rate; misbehavior detection; real-time;
Conference_Titel :
Global Communications Conference (GLOBECOM), 2014 IEEE
Conference_Location :
Austin, TX
DOI :
10.1109/GLOCOM.2014.7036878