MC-RPL: A New Routing Approach based on Multi-Criteria RPL for the Internet of Things

Farzaneh, Behnam; Ahmed, Ali Kamil; Alizadeh, Emad

doi:10.1109/iccke48569.2019.8964675

Cited by 13 publications

(6 citation statements)

References 20 publications

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“…In recent years, MCDM methods are widely used in network topics [28]. The TOPSIS method as a well-known MCDM introduced for the first time in 1981 [27].…”

Section: Topsis Methodsmentioning

confidence: 99%

A distributed trust mechanism for malicious behaviors in VANETs

Ahmed

Abdulwahed

Farzaneh

2020

IJEECS

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<p>Vehicular Ad-hoc Networks (VANETs) are one of the most important types of networks which are widely used in recent years. Along with all the benefits of Quality of Service (QoS) improvements, vulnerability analysis for this type of networks is an important issue. For instance, a Gray-hole attack decreases network performance. We proposed a novel solution to help to secure these networks against this vulnerability. The proposed method can detect and prevent the Gray-hole attack. Anywhere in the network, each node (vehicle) can distinguish between the Gray-hole attack and the failed link. Some topology related information helps us to detect attacks more accurately. Also, the proposed method uses the most reliable path in terms of link failure when there is no malicious node. In this paper, we used the TOPSIS method for choosing the most trusted node for routing intelligently. We validated our proposal using a simulation model in the NS-2 simulator. Simulation results show that the proposed method can prevent Gray-hole attack efficiently with low overhead.</p>

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“…In recent years, MCDM methods are widely used in network topics [28]. The TOPSIS method as a well-known MCDM introduced for the first time in 1981 [27].…”

Section: Topsis Methodsmentioning

confidence: 99%

A distributed trust mechanism for malicious behaviors in VANETs

Ahmed

Abdulwahed

Farzaneh

2020

IJEECS

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“…RPL routing protocol uses four types of control messages [18], [19], which are DODAG information object (DIO), DODAG information solicitation (DIS), DODAG advertisement object (DAO), destination advertisement object acknowledgment (DAO-Ack). To construct DODAG, the sink or root starts to propagate DIO messages through the network.…”

Section: Preliminaries 21 the Rpl Routing Protocolmentioning

confidence: 99%

TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decision-making

Ahmed

Farzaneh²,

Boochanpour³

et al. 2023

IJECE

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The internet of things (IoT) based on a network layer perspective includes low-power and lossy networks (LLN) that are limited in terms of power consumption, memory, and energy usage. The routing protocol used in these networks is called routing over low-power and lossy networks (RPL). Therefore, the IoT networks include smart objects that need multiple routing for their interconnections which makes traffic load balancing techniques indispensable to RPL routing protocol. In this paper, we propose a method based on fuzzy logic and the technique for the order of prioritization by similarity to the ideal solution (TOPSIS) as a well-known multi-criteria decision-making method to solve the load balancing problem by routing metrics composition. For this purpose, a combination of both link and node routing metrics namely hop count, expected transmission count, and received signal strength indicator is used. The results of simulations show that this method can increase the quality of services in terms of packet delivery ratio and average end-to-end delay.

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“…FNR: The rate of the malevolent node to total normal nodes incorrectly signed as a normal node. [21][22][23][24][25] The calculation is proved by Equation 12. PDR: This criterion represents the rate of packets that were successfully delivered to the destination.…”

Section: Dr = Tpr Tpr + Fnrmentioning

confidence: 99%

“…

italicDR = ((), \frac{italicTPR}{TPR + FNR}) * 100 where All = italicTPR + italicTNR + italicFPR + italicFNR

FPR: The FPR is determined by the total number of nodes mistakenly found as the malevolent nodes divided by the total number of usual nodes 18–20 . Hence, Equation illustrates the

italicFPR = ((), \frac{italicFPR}{FPR + TNR}) * 100, where italicTNR = ((), \frac{italicTNR}{TNR + FPR}) * 100

FNR: The rate of the malevolent node to total normal nodes incorrectly signed as a normal node 21–25 . The calculation is proved by Equation .…”

Section: Performance Evaluationmentioning

confidence: 99%

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A method based on encryption and node rating for securing the RPL protocol communications in the IoT ecosystem

Zaminkar¹,

Sarkohaki

Fotohi

2020

Int J Communication

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Summary Internet of Things (IoT) provides the possibility for milliards of devices throughout the world to communicate with each other, and data are collected autonomously. The big data generated by the devices should be managed securely. Due to security challenges, like malicious nodes, many approaches cannot respond to these concerns. In this paper, a robust hybrid method, including encryption, is used as an efficient approach for resolving the Low‐Power and Lossy Networks (RPL) protocol concerns so that the devices are connected securely. Therefore, the proposed Detection of sinkholes in RPL (DSH‐RPL) method for securing the RPL protocol comprises the four following phases: the first phase creates a reliable RPL. The second phase detects the sinkhole attack. The third phase quarantines the detected malicious node, and the fourth phase transmits data through encryption. The simulation results show that the DSH‐RPL reduces the false‐positive rate more than 18.2% and 23.1% and reduces the false‐negative rate more than 16.1% and 22.78% and it also increases the packet delivery rate more than 19.68% and 25.32% and increases the detection rate more than 26% and 31% compared to SecTrust‐RPL and IBOOS‐RPL.

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MC-RPL: A New Routing Approach based on Multi-Criteria RPL for the Internet of Things

Cited by 13 publications

References 20 publications

A distributed trust mechanism for malicious behaviors in VANETs

A distributed trust mechanism for malicious behaviors in VANETs

TFUZZY-OF: a new method for routing protocol for low-power and lossy networks load balancing using multi-criteria decision-making

A method based on encryption and node rating for securing the RPL protocol communications in the IoT ecosystem

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