RPL-Based IoT Networks under Simple and Complex Routing Security Attacks: An Experimental Study

Alsukayti, Ibrahim S.; Alreshoodi, Mohammed

doi:10.3390/app13084878

Cited by 6 publications

(2 citation statements)

References 47 publications

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“…In [49], replay attacks caused adverse impacts on energy consumption and QoS performance. The comprehensive study of these attacks in [50] also indicates the severe damages that can be realized if these attacks take more adverse forms.…”

Section: Related Workmentioning

confidence: 99%

A Lightweight Mitigation Approach against a New Inundation Attack in RPL-Based IoT Networks

Rouissat,

Belkheir,

Alsukayti

et al. 2023

Applied Sciences

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Internet of Things (IoT) networks are being widely deployed for a broad range of critical applications. Without effective security support, such a trend would open the doors to notable security challenges. Due to their inherent constrained characteristics, IoT networks are highly vulnerable to the adverse impacts of a wide scope of IoT attacks. Among these, flooding attacks would cause great damage given the limited computational and energy capacity of IoT devices. However, IETF-standardized IoT routing protocols, such as the IPv6 Routing Protocol for Low Power and Lossy Networks (RPL), have no relevant security-provision mechanism. Different variants of the flooding attack can be easily initiated in RPL networks to exhaust network resources and degrade overall network performance. In this paper, a novel variant referred to as the Destination Information Object Flooding (DIOF) attack is introduced. The DIOF attack involves an internal malicious node disseminating falsified information to instigate excessive transmissions of DIO control messages. The results of the experimental evaluation demonstrated the significant adverse impact of DIOF attacks on control overhead and energy consumption, which increased by more than 500% and 210%, respectively. A reduction of more than 32% in Packet Delivery Ratio (PDR) and an increase of more than 192% in latency were also experienced. These were more evident in cases in which the malicious node was in close proximity to the sink node. To effectively address the DIOF attack, we propose a new lightweight approach based on a collaborative and distributed security scheme referred to as DIOF-Secure RPL (DSRPL). It provides an effective solution, enhancing RPL network resilience against DIOF attacks with only simple in-protocol modifications. As the experimental results indicated, DSRPL guaranteed responsive detection and mitigation of the DIOF attacks in a matter of a few seconds. Compared to RPL attack scenarios, it also succeeded in reducing network overhead and energy consumption by more than 80% while maintaining QoS performance at satisfactory levels.

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Section: Related Workmentioning

confidence: 99%

A Lightweight Mitigation Approach against a New Inundation Attack in RPL-Based IoT Networks

Rouissat,

Belkheir,

Alsukayti

et al. 2023

Applied Sciences

Self Cite

View full text Add to dashboard Cite

show abstract

“…In load adjustment, the majority of the work focused on the boundaries, for example, youngster count and line usage to adjust the heap in the organization. Be that as it may, these two boundaries are not adequate to adjust the heap solidly (20)(21)(22)(23) . In the predetermined number of works, bunch-based directing is acted in the RPL organization to adjust the heap and diminish energy utilization (24) .…”

Section: Introductionmentioning

confidence: 99%

Adaptive RPL Routing Optimization Model for Multimedia Data Transmission using IOT

Shashidhar,

Thanuja,

Kunabeva

2024

IJST

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Objectives: The main objectives of this research endeavor encompass the development of the Adaptive RPL Optimization (ARPLO) model to enhance data transmission efficiency within IoT networks. This includes constructing a grid-based network structure optimized for data transfer, selecting the most suitable nodes as grid head nodes to maximize network lifespan while minimizing energy consumption, implementing an innovative objective function-driven approach to optimize parent node selection, and integrating an Adaptive Deep Neural Network (ADNN) to accurately classify medical data. Methods: The research methodology entails several key steps. A grid-based network structure is established with IoT nodes and root nodes, where a DODAG process incorporating DIO messages is utilized for node ranking. To enhance energy efficiency, the Trickle algorithm is employed for control message optimization. Grid head nodes are chosen based on metrics such as root node fairness, residual energy, and load influence index. The novel Middle Order Optimal Routing (MOOR) objective function is utilized to optimize routing decisions. ADNN is implemented for precise medical data classification. The proposed model's performance is evaluated through simulation in a Python environment. Findings: The research findings demonstrate that the ARPLO model yields notable benefits compared to existing models. It achieves higher energy efficiency, improved throughput, enhanced packet delivery ratio (PDR), and an extended network lifespan. The Trickle algorithm contributes to efficient control message optimization. The MOOR-based routing approach improves multimedia medical data transfer. Moreover, the integration of ADNN enhances the accuracy of data classification, particularly in healthcare applications. The research outcomes align with the broader field's existing values and reports while offering novel insights that contribute to enhancing the existing knowledge base. ARPLO protocol performance reveals that there is increase of throughput of 31.2%, PDR by 7.12%, lifetime of 10.7 % with reduction of energy consumption by 12.72%, control overhead by 31.01% and end-to-end delay by 33.01%. Novelty: The novelty of this research lies in its comprehensive approach that integrates a grid-based network structure, MOOR-based optimization, and ADNN-based classification. The incorporation of the Trickle algorithm for energy-efficient communication is an innovative feature. The introduction of new metrics for grid head node selection, along with the application of the MOOR objective function for multimedia medical data routing, showcases the research's innovative contributions. Keywords: Internet of Things (IoT), RPL (Routing Protocol for LowPower and Lossy Networks), Optimization, Routing, Multimedia, Healthcare

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RPL-based attack detection approaches in IoT networks: review and taxonomy

Alfriehat,

Anbar,

Aladaileh

et al. 2024

Artif Intell Rev

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RPL-Based IoT Networks under Simple and Complex Routing Security Attacks: An Experimental Study

Cited by 6 publications

References 47 publications

A Lightweight Mitigation Approach against a New Inundation Attack in RPL-Based IoT Networks

A Lightweight Mitigation Approach against a New Inundation Attack in RPL-Based IoT Networks

Adaptive RPL Routing Optimization Model for Multimedia Data Transmission using IOT

RPL-based attack detection approaches in IoT networks: review and taxonomy

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