Real time performance analysis of secure IoT protocols for microgrid communication

Kondoro, Aron; Dhaou, Imed Ben; Tenhunen, Hannu; Mvungi, Nerey H.

doi:10.1016/j.future.2020.09.031

Cited by 49 publications

(33 citation statements)

References 14 publications

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“…Capacity (C) in Equation 2 states that any small changes in overloadcoefficient (δ ≥ 0) which leads to a change of traffic load will bring the violation of capacity. In our IoT application, a microgrid is an autonomous system that can control and manage itself [23]. Sometimes in an energy microgrid, consumers receive heat energy for heating and cooling in addition to electricity.…”

Section: Problem Statementmentioning

confidence: 99%

“…Further, Microgrids are vulnerable to abnormalities due to small inherent inertia. Therefore, the stability of microgrids becomes a challenge after disrupting power systems [10,23].…”

Section: Problem Statementmentioning

confidence: 99%

“…After completing the set-up phase and broadcasting the configuration information to all nodes, we run the steady-state, Return Locating Next-Hop(g_best particle(i) ) 23: end procedure which is executed at the sink. In IoT networks with multihop communication, nodes may fail due to the application state [30,38].…”

Section: Steady Statementioning

confidence: 99%

“…In this work, we are focusing on microgrid applications as one of the most critical IoT applications that could be affected by cascading failure [23]. In general, IoT network is a proper solution for microgrid applications in order to manage energy and traffic load, especially when microgrids are equipped with renewable sources of energy [17,18,23]. These resources are usually located in harsh environments and complex places.…”

Section: Introductionmentioning

confidence: 99%

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REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks

2021

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There has been tremendous growth in the Internet of Things (IoT) technologies, and many new applications have emerged. However, cascading failure as one of the major issues in such constrained networks have been neglected. In this paper, we apply an effective clustering approach dubbed as REFIT to enhance network topology robustness via nodes' residual energy. The REFIT protocol divides the network processes into two stages, (i) setup state and (ii) steady state. The Cluster Head (CH) selection method determines the supreme set of CHs that balances load distribution. The routing method is developed with the modified Particle Swarm Optimization (PSO) algorithm and the objective function to find the supreme set of Relay Nodes (RNs). These complete methods are combined into a setup state to construct an optimal routing tree that links these CHs to the sink via RNs. In steady state, we model the routing tree to Conditional Directed Acyclic Graph (C-DAG) infrastructure that leads to shortcut routes. Simulation results on MATLAB Simulink have demonstrated that compared with the state-of-the-art works, REFIT can significantly promote network robustness against cascading failure.

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Section: Problem Statementmentioning

confidence: 99%

“…Further, Microgrids are vulnerable to abnormalities due to small inherent inertia. Therefore, the stability of microgrids becomes a challenge after disrupting power systems [10,23].…”

Section: Problem Statementmentioning

confidence: 99%

Section: Steady Statementioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

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REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks

2021

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“…opportunity for IoT devices in an SDMG, there is need to discuss the methods of securing IoT protocols coupling the IoT integration in MGs. The properties of IoT security protocols and their impact on the security requirements of smart grids and MGs have been investigated [62]. Results showed that the required security protocols increased in latency and traffic overhead by about three (3) times.…”

Section: ) Security Managementmentioning

confidence: 99%

Software-Defined Power Grids: A Survey on Opportunities and Taxonomy for Microgrids

et al. 2021

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Future generation power grids will require the introduction and deployment of distributed energy resources to meet modern day load requirements. Consequently, we expect to see a rise in microgrids (MGs) existing as part of the main grid (grid-connected) or independent (islanded). Contained in these microgrids are a combination of energy resources such as solar, wind and fossil-fuels coupled with storage devices, electric vehicles and smart devices supporting prosumer operation. However, the addition of renewable energy resources would mean fluctuations in energy supply which would cause power system instability if not managed effectively. Hence, to maximize the management flexibility of MGs, the concept of microgrid software-definition is introduced. A concept that can be looked at as giving the microgrid an operating system to improve operation response and event detection by maintaining a global view of the network. This paper therefore critically analyses what this entails by presenting an architecture for Software-Defined Microgrids and discussing the management opportunities that softwarization of the MG introduces. We also highlight the design requirements and associated challenges in implementing and deploying SDMGs.INDEX TERMS Energy balancing, grid resiliency, microgrids, power grid management, software-defined networking, smart grids.

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A novel framework approach for intrusion detection based on improved critical feature selection in Internet of Things networks

Hariprasad

Deepa

2022

Concurrency and Computation

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With the convergence of the Internet of Things (IoT), 5G, and artificial intelligence, the number of security violations and disturbances on IoT devices and networks has increased. Traditional intrusion detection systems (IDS) are inadequate to handle and detect attacks. This article proposes an improved critical feature selection (ICFS) algorithm with an ensemble learning (EL) for IDS in IoT-Message queuing telemetry transport (MQTT) network. The proposed framework includes four major parts: (i) The RPIMQTTSET dataset is created using three raspberry pi devices for generating the regular and attack features. (ii) An ICFS algorithm is proposed to select the optimized features from the original dataset, and the optimized features have been validated with the help of the Tanimoto coefficient. (iii) SMOTETomek is applied for balancing the dataset to improve the detection rate of attacks. (iv) Generation of a K-fold cross-validated attack detection model utilizing an EL method such as K-nearest neighbor, eXtreme Gradient Boosting, and random forest. Experimental results show less computational complexity in selecting features, training, and testing the dataset in the proposed network. The proposed model has training accuracy over 99% and testing accuracy over 92%, and it uses fewer redundant features than previous state-of-the-art methodologies.

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Real time performance analysis of secure IoT protocols for microgrid communication

Cited by 49 publications

References 14 publications

REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks

REFIT: Robustness Enhancement Against Cascading Failure in IoT Networks

Software-Defined Power Grids: A Survey on Opportunities and Taxonomy for Microgrids

A novel framework approach for intrusion detection based on improved critical feature selection in Internet of Things networks

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