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Using Trust to Establish a Secure Routing Model in Cognitive Radio Network.

Zhang G, Chen Z, Tian L, Zhang D - PLoS ONE (2015)

Bottom Line: At the same time, according to the trust classification, different responses are made specific to their service requests.By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated.Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.

View Article: PubMed Central - PubMed

Affiliation: State Key Lab of Integrated Service Networks, Xidian University, Xi'an, Shannxi, China; College of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, Hebei, China.

ABSTRACT
Specific to the selective forwarding attack on routing in cognitive radio network, this paper proposes a trust-based secure routing model. Through monitoring nodes' forwarding behaviors, trusts of nodes are constructed to identify malicious nodes. In consideration of that routing selection-based model must be closely collaborative with spectrum allocation, a route request piggybacking available spectrum opportunities is sent to non-malicious nodes. In the routing decision phase, nodes' trusts are used to construct available path trusts and delay measurement is combined for making routing decisions. At the same time, according to the trust classification, different responses are made specific to their service requests. By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated. Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.

No MeSH data available.


Trust changes of neighboring nodes.
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pone.0139326.g006: Trust changes of neighboring nodes.

Mentions: Fig 6 shows the change process of trust evaluation of node i in TSRM on three neighboring nodes. Node j honestly forwards data packets from node i all the time and the trust evaluation of node i to it gradually increases. Finally Node j is listed in trusted nodes. Because of selective forwarding attack behaviors, the trust evaluation of node i based on reward and punishment mechanism to neighboring nodes k and l sharply decreases. Nodes k and l only can slowly improve the trust evaluation through honest forwarding. Due to the continuously honest forwarding of node k, the trust evaluation of node i increases later and node k is regarded as common nodes. Because node l has repeated attack behaviors after honest forwarding in certain time and the trust evaluation of node i decreases to certain threshold and node l is regarded as malicious nodes. In the trust-based routing model, malicious node l will not be chosen as the next-hop forwarding data of node i and its service request also cannot be satisfied. For the different forwarding behaviors of neighboring nodes, nodes will make different trust evaluations. At the same time, the malicious behaviors of untrusted nodes are punished severely so as to stimulate the node cooperation in routes.


Using Trust to Establish a Secure Routing Model in Cognitive Radio Network.

Zhang G, Chen Z, Tian L, Zhang D - PLoS ONE (2015)

Trust changes of neighboring nodes.
© Copyright Policy
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4589414&req=5

pone.0139326.g006: Trust changes of neighboring nodes.
Mentions: Fig 6 shows the change process of trust evaluation of node i in TSRM on three neighboring nodes. Node j honestly forwards data packets from node i all the time and the trust evaluation of node i to it gradually increases. Finally Node j is listed in trusted nodes. Because of selective forwarding attack behaviors, the trust evaluation of node i based on reward and punishment mechanism to neighboring nodes k and l sharply decreases. Nodes k and l only can slowly improve the trust evaluation through honest forwarding. Due to the continuously honest forwarding of node k, the trust evaluation of node i increases later and node k is regarded as common nodes. Because node l has repeated attack behaviors after honest forwarding in certain time and the trust evaluation of node i decreases to certain threshold and node l is regarded as malicious nodes. In the trust-based routing model, malicious node l will not be chosen as the next-hop forwarding data of node i and its service request also cannot be satisfied. For the different forwarding behaviors of neighboring nodes, nodes will make different trust evaluations. At the same time, the malicious behaviors of untrusted nodes are punished severely so as to stimulate the node cooperation in routes.

Bottom Line: At the same time, according to the trust classification, different responses are made specific to their service requests.By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated.Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.

View Article: PubMed Central - PubMed

Affiliation: State Key Lab of Integrated Service Networks, Xidian University, Xi'an, Shannxi, China; College of Information Science and Engineering, Hebei University of Science and Technology, Shijiazhuang, Hebei, China.

ABSTRACT
Specific to the selective forwarding attack on routing in cognitive radio network, this paper proposes a trust-based secure routing model. Through monitoring nodes' forwarding behaviors, trusts of nodes are constructed to identify malicious nodes. In consideration of that routing selection-based model must be closely collaborative with spectrum allocation, a route request piggybacking available spectrum opportunities is sent to non-malicious nodes. In the routing decision phase, nodes' trusts are used to construct available path trusts and delay measurement is combined for making routing decisions. At the same time, according to the trust classification, different responses are made specific to their service requests. By adopting stricter punishment on malicious behaviors from non-trusted nodes, the cooperation of nodes in routing can be stimulated. Simulation results and analysis indicate that this model has good performance in network throughput and end-to-end delay under the selective forwarding attack.

No MeSH data available.