Robust detection of selfish misbehavior in wireless networks

Toledo, Alberto Lopéz; Wang, Xiaodong

doi:10.1109/jsac.2007.070807

Cited by 78 publications

(79 citation statements)

References 18 publications

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“…We perform the test when the station is near and far from the AP (near and f ar, respectively), and for p c ranging from 0 (no capture) to 1 (the frame from the near station always captures the medium). The results show that the assumptions made in [7] lead to quite low performance if a station benefits from the radio conditions. More specifically, the TLW mechanisms largely deviates from the target P F A if a station captures the channel in just 25% of the collisions, leading to P F A = 0.22.…”

Section: Performance Evaluationmentioning

confidence: 98%

“…Note that, although [7] also uses a K-S test on the sample distribution of timeslots, there are at least two major differences between the two approaches: 1) Our proposal does not require the estimation of any WLAN parameter: in [7], authors have to compute the so called collision factor γ (the average number of stations involved in a collision), and then use a polynomial regression model to estimate the collision probabilityp c . 2) Our proposal does not make any assumption about the radio conditions.…”

Section: Detecting Selfish Edca Configurationsmentioning

confidence: 99%

“…2) Our proposal does not make any assumption about the radio conditions. In [7], authors assume there are no losses due to noise and that in case of a collision all frames are lost. However, this is not the case for real WLANs, where the capture effect (in case of a collision, one of the frames may get through due to its larger power) is quite common -see, e.g., [2].…”

Section: Detecting Selfish Edca Configurationsmentioning

confidence: 99%

“…Results are presented in Table I for the algorithm of [7] (TLW) and the one presented in this letter (Ours). We perform the test when the station is near and far from the AP (near and f ar, respectively), and for p c ranging from 0 (no capture) to 1 (the frame from the near station always captures the medium).…”

Section: Performance Evaluationmentioning

confidence: 99%

“…• The approach of [7] is built on top of some strong radio assumptions that leads to unexpected poor performance for realistic scenarios. Digital Object Identifier XXX…”

Section: Introductionmentioning

confidence: 99%

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Detecting selfish configurations in 802.11 WLANs

et al. 2010

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Abstract-Lately, there has been an increase in the number of IEEE 802.11 devices that provide users with the ability to modify the MAC parameters or do not conform to the standard specification. This increases the risk of having a WLAN with selfish stations that, through the CSMA/CA parameters, obtain a larger share of the resources at the expense of well-behaved users. In this letter we propose a mechanism to detect these selfish stations that, unlike previous approaches, is not based on heuristics nor makes any assumption about radio conditions.

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Section: Performance Evaluationmentioning

confidence: 98%

Section: Detecting Selfish Edca Configurationsmentioning

confidence: 99%

Section: Detecting Selfish Edca Configurationsmentioning

confidence: 99%

Section: Performance Evaluationmentioning

confidence: 99%

“…• The approach of [7] is built on top of some strong radio assumptions that leads to unexpected poor performance for realistic scenarios. Digital Object Identifier XXX…”

Section: Introductionmentioning

confidence: 99%

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Detecting selfish configurations in 802.11 WLANs

et al. 2010

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Characterizing the greedy behavior in wireless ad hoc networks

Djahel

Naït‐Abdesselam

Turgut

2011

Security Comm Networks

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While the problem of greedy behavior at the MAC layer has been widely explored in the context of wireless local area networks (WLAN), its study for multi-hop wireless networks still almost an unexplored and unexplained problem. Indeed, in a wireless local area network, an access point mostly forwards packets sent by wireless nodes over the wired link. In this case, a greedy node can easily get more bandwidth share and starve all other associated contending nodes by manipulating intelligently MAC layer parameters. However, in wireless ad hoc environment, all packets are transmitted in a multi-hop fashion over wireless links. In this case, an attempting greedy node, if it behaves similarly as in a WLAN, trying to starve all its neighbors, then its next hop forwarder will be also prevented from forwarding its own traffic, which leads obviously to an end to end throughput collapse. In this paper, we show that in order to have a more beneficial greedy behavior in wireless ad hoc network, a node must adopt a different approach than in WLAN to achieve a better performance of its own flows. Then, we present a new strategy to launch such a greedy attack in a proactive routing based wireless ad hoc network. A detailed description of the proposed strategy is provided along with its validation through extensive simulations. The obtained results show that a greedy node, applying the defined strategy, can gain more bandwidth than its neighbors and keep the end-to-end throughput of its own flows highly reasonable.

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

Tang

Cheng

2013

Intrusion Detection for IP-Based Multimedia Communications Over Wireless Networks

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Robust detection of selfish misbehavior in wireless networks

Cited by 78 publications

References 18 publications

Detecting selfish configurations in 802.11 WLANs

Detecting selfish configurations in 802.11 WLANs

Characterizing the greedy behavior in wireless ad hoc networks

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

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