Mitigating malicious nodes using trust and reputation based model in wireless sensor networks
Wireless sensor network (WSN) is one of the promising network infrastructures for many applications such as healthcare monitoring, environmental monitoring, structural health monitoring, homeland security, military and battlefield surveillance. These applications are basically involve in monitori...
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| Main Author: | |
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| Format: | Thesis |
| Language: | English |
| Published: |
2018
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| Subjects: | |
| Online Access: | http://psasir.upm.edu.my/id/eprint/68812/1/FSKTM%202018%2020%20IR.pdf |
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| Summary: | Wireless sensor network (WSN) is one of the promising network infrastructures for
many applications such as healthcare monitoring, environmental monitoring,
structural health monitoring, homeland security, military and battlefield surveillance.
These applications are basically involve in monitoring of sensitive information such
as tracking of enemy movement and patient’s health information. Therefore,
delivering these information becomes one of the challenging issues in WSNs.
Generally, in WSNs, data are forwarded via multi-hop manner and because of this, the
security of these data faced several challenges due the malicious nodes that could
potentially be selected as one of the intermediate nodes. Trust and reputation-based
technique has been acknowledged as one of the promising solutions to overcome this
problem. However, many of existing trust and reputation models in WSNs are insecure
due to inaccurate node’s trustworthiness evaluation which cause node to accidentally
choose a malicious node during the data forwarding process. This problem occurs due
to the limited number of trust information used to compute node’s trustworthiness
value. In addition, to increase the accuracy of node trustworthiness evaluation, node
in the network solicits more information through recommendations from other nodes
in the network. However, information collected using recommendations are
vulnerable to dishonest recommendation attacks that can potentially mislead the trust
computation engine. Most, if not all, existing models in trust and reputation domain
are lack in providing sufficient behavioral-based trust information. Many of them
focus too much on Quality-of-Service (QoS) types of trust information and less
consideration has been put on other sources of trust information such as in Mobile Ad
hoc Networks (MANETs) and Online Social Networks (OSNs). This significantly
contributes to the scarcity of trust information which leads to poor network and
security performances. This research aims to increase the accuracy of node
trustworthiness evaluation process in order to helps node to make more informed
decision prior to establish secure communications. In order to achieve this, different sets of trust information including QoS, OSNs and ant colony system (ACS) algorithm
are proposed to improve the selection of trustworthy node. In this research, three
models have been proposed namely Trust and Reputation Model for Wireless Sensor
Networks (TReM-WSN), Recommendation-based Trust Model (RecommTM) and a
multidimensional Trust and Reputation Model using Social, Quality of service and
Ant colony system (TRM-SQA). The effectiveness of each of these models in
evaluating node’s trustworthiness and mitigating malicious nodes, as well as their
influence on network and security performances will be tested and validated through
simulation. The network and security performances such as Packet Delivery Ratio
(PDR), packet loss, selection accuracy, path length, node’s trust value, recognition
proportion (RP), false negative proportion (FNP) and false positive proportion (FPP)
will be evaluated during the simulation process. Results gained from the performance
evaluation show that the proposed models able to improve PDR, selection accuracy,
path length, node’s trust value and significantly reduced the packet loss rate. In
addition, the problems related to RP, FNP and FPP are also have been successfully
addressed. |
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