DDoS attack aware environment with secure clustering and routing based on RPL protocol operation

Alabsi, Basim Ahmad; Anbar, Mohammed; Manickam, Selvakumar; Elejla, Omar E.

doi:10.1049/iet-cds.2018.5079

Cited by 10 publications

(3 citation statements)

References 32 publications

(40 reference statements)

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“…There are many researches on secure and trusted routing in Wireless Sensor Network (WSN). Alabsi et al proposed a DDoS detection method based on Ant Colony Optimization (ACO) algorithm for WSN to find the routing nodes under attack by analyzing packet characteristics such as IP, protocol types, destination address [20]. The nodes suffering from DDoS attacks will be avoided for trusted routing.…”

Section: B Trusted Routing Methodsmentioning

confidence: 99%

A Trusted Resource-Based Routing Algorithm With Entropy Estimation in Integrated Space-Terrestrial Network

Guo

Wang

Zhi³

et al. 2020

IEEE Access

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Integrated Space-Terrestrial Network (ISTN) can effectively improve the global communication coverage and SDN framework in ISTN has emerged as a promising solution to guarantee the Quality of Service (QoS). At present, the researches on routing algorithm are mainly focused on the QoS parameters about resource availability and do not consider the impact of the network attacks comprehensively, such as DDoS attack. Plenty of available resources will be occupied by network attacks and normal traffic may be blocked incorrectly by attack defense solutions. In this paper, we propose a Trusted Routing (TR) model based on Trusted Resource Matrix (TRM) to protect the normal traffic from network attacks in ISTN. In the process, the SDN controller constructs the characteristic matrices by collecting the state information of each routing node and the entropy estimation method which describes the changes of traffic characteristics is used to determine whether a routing node is suffering from network attacks. Corresponding trust values are allocated to the routing nodes for constructing TRM and trusted transmission paths are discovered by the TR model. Based on the comprehensive consideration of available and trusted resources, a Hybrid Routing (HR) model is proposed, taking into account the traditional QoS parameters and TRM. In the simulation experiments, the TR and HR models-based algorithms are evaluated. The experimental results show that TR and HR algorithms can effectively avoid the routing nodes suffering from network attacks and improve the communication QoS. When considering a scenario of a single attacked node under resource constraints, the average packet pass rate of HR algorithm is about 7.0% higher than that of TR algorithm and about 52.1% higher than that of traditional QoS algorithm.

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Section: B Trusted Routing Methodsmentioning

confidence: 99%

A Trusted Resource-Based Routing Algorithm With Entropy Estimation in Integrated Space-Terrestrial Network

Guo

Wang

Zhi³

et al. 2020

IEEE Access

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“…The sensed data is forwarded toward the root, i.e., the IoT gateway, in this proposed work. In general, RPL uses four significant control messages for constructing DODAG[21]. The control messages are described as follows, DODAG Information Object (DIO): The root nodes presented in the network initiate this message to construct the DODAG.…”

mentioning

confidence: 99%

Software Defined Network for Energy Efficiency in IoT and RPL Networks

Gasouma

Yusof

Mubarakali

et al. 2023

Preprint

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Today's most significant developing technology is the Internet of Things (IoT), and investigating it is a hot issue in information technology. The Internet Engineering Task Force (IETF) in RFC6550 defined the IPv6 Routing Protocol for Low-Power and Lossy Networks (RPL), one of the IoT's core routing protocols, and it is the only standard protocol that assists the routing process in Low Power and Lossy Networks (LLNs) of IoT applications. LLNs are connecting smart devices to the Internet to monitor, control, or exchange data. These smart devices are tiny with limited battery capacity and power supply, and it is suffering from excessive energy consumption. This network issue may be addressed with innovative flexible network topology using Software-Defined networks. Our work proposes an (LBC-NDFA) algorithm for software-defined RPL networks to reduce the number of RPL control messages and increase energy efficiency using a Limit based Broadcast Control (LBC) approach that modified the Destination Oriented Directed Acyclic Graph (DODAG) Information Object (DIO) control message format and used the Non-Deterministic Finite Automata (NDFA) algorithm to determine whether a DIO message needs to be broadcasted. Using network simulator NS3, we assess the results. The results of our experiments show the viability of our proposal with decreased control overhead, and control messages, and reduced energy consumption by 40% and 60% with compared works.

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“…• DDoS Flooding Attack: In a DDoS flooding attack, various malicious nodes target the network nodes with vast amounts of traffic to interrupt the normal operation of the network services. This attack also increases communication overhead and overwhelms the power resources of the sensor nodes[63,76,77]. This attack happens when the malicious node dislocates the network routing path by selectively forwarding some of the packets in the network while leaving the rest forwarded to the original destination[21].…”

mentioning

confidence: 99%

A Systematic Literature Review on Machine and Deep Learning Approaches for Detecting Attacks in RPL-Based 6LoWPAN of Internet of Things

Al-Amiedy

Anbar

Belaton

et al. 2022

Sensors

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The IETF Routing Over Low power and Lossy network (ROLL) working group defined IPv6 Routing Protocol for Low Power and Lossy Network (RPL) to facilitate efficient routing in IPv6 over Low-Power Wireless Personal Area Networks (6LoWPAN). Limited resources of 6LoWPAN nodes make it challenging to secure the environment, leaving it vulnerable to threats and security attacks. Machine Learning (ML) and Deep Learning (DL) approaches have shown promise as effective and efficient mechanisms for detecting anomalous behaviors in RPL-based 6LoWPAN. Therefore, this paper systematically reviews and critically analyzes the research landscape on ML, DL, and combined ML-DL approaches applied to detect attacks in RPL networks. In addition, this study examined existing datasets designed explicitly for the RPL network. This work collects relevant studies from five major databases: Google Scholar, Springer Link, Scopus, Science Direct, and IEEE Xplore® digital library. Furthermore, 15,543 studies, retrieved from January 2016 to mid-2021, were refined according to the assigned inclusion criteria and designed research questions resulting in 49 studies. Finally, a conclusive discussion highlights the issues and challenges in the existing studies and proposes several future research directions.

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DDoS attack aware environment with secure clustering and routing based on RPL protocol operation

Cited by 10 publications

References 32 publications

A Trusted Resource-Based Routing Algorithm With Entropy Estimation in Integrated Space-Terrestrial Network

A Trusted Resource-Based Routing Algorithm With Entropy Estimation in Integrated Space-Terrestrial Network

Software Defined Network for Energy Efficiency in IoT and RPL Networks

A Systematic Literature Review on Machine and Deep Learning Approaches for Detecting Attacks in RPL-Based 6LoWPAN of Internet of Things

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