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Mitigating malicious nodes using trust and reputation based model in wireless sensor networks


Abdullah, Muhammad Daniel Hafiz (2018) Mitigating malicious nodes using trust and reputation based model in wireless sensor networks. PhD thesis, Universiti Putra Malaysia.

Abstract / Synopsis

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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Additional Metadata

Item Type: Thesis (PhD)
Subject: Wireless sensor nodes - Security measures - Research
Subject: Wireless sensor networks
Call Number: FSKTM 2018 20
Chairman Supervisor: Associate Professor Zurina Mohd Hanapi, PhD
Divisions: Faculty of Computer Science and Information Technology
Depositing User: Ms. Nur Faseha Mohd Kadim
Date Deposited: 18 Jun 2019 10:58
Last Modified: 18 Jun 2019 10:58
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