Evaluation and Prevention of MAC Layer Misbehaviours in Public Wireless Hotspots

Alocious, Chaminda; Xiao, Hannan; Christianson, Bruce; Malcolm, James A.

doi:10.1109/cit/iucc/dasc/picom.2015.276

Cited by 3 publications

(4 citation statements)

References 13 publications

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“…In [4] they have analysed and simulated the RTS/CTS DoS attack variants in 802.11 networks, which is one type of low rate DoS attack that capable to exploit the medium reservation mechanism of IEEE 802.11 through duration field. Also, in [5] [6] [7] has conducted an evaluation for greedy receiver misbehaviour in IEEE 802.11 Hotspots, they have identified a range of greedy receiver misbehaviours, and quantify their damage using both simulation and testbed experiments.…”

Section: B Ieee 80211 Mac Protocol Misbehavioursmentioning

confidence: 99%

“…However, this approach only capable to detect sender misbehaviours in a trusted Access Point (AP) environment. The research done by [5] demonstrates the weakness of such detection mechanisms with the existence of malicious/misbehaving AP and discusses potential prevention strategies.…”

Section: B Ieee 80211 Mac Protocol Misbehavioursmentioning

confidence: 99%

“…The equations (5) (6) demonstrate the trust value (Ttv) calculations by the neighbour node. Firstly, the neighbours calculates the misbehaviour factor (Mf) based on (5).…”

Section: Trust Management With Common Neighbours/receiversmentioning

confidence: 99%

“…In equation (5) the Mf is the ratio between the average deviation (receiver reported deviation (Rec Act − Snd Exp ) and neighbour's observed deviation (N br Act − Snd Exp )) backoff slots to the sender's expected backoff value (Snd Exp ). This will give a conservative value for calculating the final trust value which starts with 100 % maximum value for all the nodes, then consequently varies based on their behaviours in every communication.…”

Section: Trust Management With Common Neighbours/receiversmentioning

confidence: 99%

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Resilient misbehaviour detection MAC protocol (MD-MAC) for distributed wireless networks

Alocious

Xiao

Christianson

2016

2016 IEEE Wireless Communications and Networking Conference

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Wireless network security requirements are becoming more important and critical. The modern network security architectures require more attention to provide security in each network layer. This will require understanding of protocol vulnerabilities in existing protocol architectures. However, providing security requirements are not just limited to confidentiality and integrity, also availability and fairness are important security elements. IEEE 802.11 MAC protocol is one of the most common standard in modern day networks and has been designed without a consideration for providing security protection at MAC layer. IEEE 802.11 assumes all the nodes in the network are cooperative. However, nodes may purposefully misbehave in order to obtain extra bandwidth, conserve resources and disrupt network performance. This research proposes a Misbehaviour Detection MAC protocol (MD-MAC) to address the problematic scenarios of MAC layer misbehaviours, which takes a novel approach to detect misbehaviours in Mobile Adhoc Networks (MANETs). The MD-MAC modifies the CSMA/CA protocol message exchange and uses verifiable backoff value generation mechanism with an incorporated trust model which is suitable for distributed networks. The MD-MAC protocol has been implemented and evaluated in ns2, simulation results suggest that the protocol is able to detect misbehaving wireless nodes in a distributed network environment.

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Section: B Ieee 80211 Mac Protocol Misbehavioursmentioning

confidence: 99%

Section: B Ieee 80211 Mac Protocol Misbehavioursmentioning

confidence: 99%

“…The equations (5) (6) demonstrate the trust value (Ttv) calculations by the neighbour node. Firstly, the neighbours calculates the misbehaviour factor (Mf) based on (5).…”

Section: Trust Management With Common Neighbours/receiversmentioning

confidence: 99%

Section: Trust Management With Common Neighbours/receiversmentioning

confidence: 99%

See 2 more Smart Citations