Trust-based secure clustering in WSN-based intelligent transportation systems

Gaber, Tarek; Abdelwahab, Sarah; Elhoseny, Mohamed; Hassanien, Aboul Ella

doi:10.1016/j.comnet.2018.09.015

Cited by 141 publications

(55 citation statements)

References 21 publications

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“…On this basis, TOU pricing is to price the electricity selling price of different regions in different time periods. According to the peak and valley situation of the traffic flow and the working efficiency of the charging station in different periods, and considering the objectives of user benefit, operator benefit, and grid fluctuation and multiple constraints, the optimal charging price of different regions in different time periods is determined by comprehensive analysis [50]. us, we can achieve differentiated pricing strategies in different regions for different time periods.…”

Section: Case Backgroundmentioning

confidence: 99%

Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

Niu

Yan

et al. 2020

Journal of Advanced Transportation

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Considering that the charging behaviors of users of electric vehicles (EVs) (including charging time and charging location) are random and uncertain and that the disorderly charging of EVs brings new challenges to the power grid, this paper proposes an optimal electricity pricing strategy for EVs based on region division and time division. Firstly, by comparing the number of EVs and charging stations in different districts of a city, the demand ratio of charging stations per unit is calculated. Secondly, according to the demand price function and the principle of profit maximization, the charging price between different districts of a city is optimized to guide users to charge in districts with more abundant charging stations. Then, based on the results of the zonal pricing strategy, the time-of-use (TOU) pricing strategy in different districts is discussed. In the TOU pricing model, consumer satisfaction, the profit of power grid enterprises, and the load variance of the power grid are considered comprehensively. Taking the optimization of the comprehensive index as the objective function, the TOU pricing optimization model of EVs is constructed. Finally, the nondominated sorting genetic algorithm (NSGA-II) is introduced to solve the above optimization problems. The specific data of EVs in a municipality directly under the Central Government are taken as examples for this analysis. The empirical results demonstrate that the peak-to-valley ratio of a certain day in the city is reduced from 56.8% to 43% by using the optimal pricing strategy, which further smooth the load curve and alleviates the impact of load fluctuation. To a certain extent, the problem caused by the uneven distribution of electric vehicles and charging stations has been optimized. An orderly and reasonable electricity pricing strategy can guide users to adjust charging habits, to ensure grid security, and to ensure the economic benefits of all parties.

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Section: Case Backgroundmentioning

confidence: 99%

Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

Niu

Yan

et al. 2020

Journal of Advanced Transportation

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“…The trust levels are used to identify malicious nodes. A clustering based model that uses trust factors for routing was proposed by Gaber et al [14]. This work uses the Bat Optimization Algorithm for identifying the cluster heads.…”

Section: Ajainulabudeen Mmohamed Surputheenmentioning

confidence: 99%

Trust based Secure and Energy Efficient Routing using ACO for WSN

Jainulabudeen*,

Surputheen

2019

IJRTE

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Secure and energy efficient routing is one of the major requirements of the WSN models. This is due to the resource constrained environments and remotely deployed conditions. This work proposes an effective model that ensures security and energy efficiency during the routing process in a WSN. The proposed model modifies the Ant Colony Optimization algorithm to perform routing based on these multiple objectives. The proposed model uses trust as the major component to provide security, and the randomness associated with the metaheuristic nature of the model enables uniform usage of all sensor nodes. This also extends the network lifetime, making the proposed model highly efficient and deployable in real-time networks. Experiments and comparisons also indicate that the proposed model exhibits shorter time requirements and provides more optimized paths compared to models in literature.

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“…Apart from the single protocol layer attack, there is another type of attack called as cross-layer attack where multiple layers are attacked [15][16][17]. IDS plays an essential role in securing the WSN as a second wall, where it detects the misbehavior of the nodes that violates the security mechanisms [18][19][20][21][22][23]. In WSN, it is difficult to use complex security mechanisms because it increases the energy consumption of a SN.…”

Section: Introductionmentioning

confidence: 99%

LB-IDS: Securing Wireless Sensor Network Using Protocol Layer Trust-Based Intrusion Detection System

Ghugar

Pradhan

Bhoi

et al. 2019

Journal of Computer Networks and Communications

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Wireless sensor network (WSN) faces severe security problems due to wireless communication between the nodes and open deployment of the nodes. The attacker disrupts the security parameters by launching attacks at different layers of the WSN. In this paper, a protocol layer trust-based intrusion detection system (LB-IDS) is proposed to secure the WSN by detecting the attackers at different layers. The trust value of a sensor node is calculated using the deviation of trust metrics at each layer with respect to the attacks. Mainly, we consider trustworthiness in the three layers such as physical layer trust, media access control (MAC) layer trust, and network layer trust. The trust of a sensor node at a particular layer is calculated by taking key trust metrics of that layer. Finally, the overall trust value of the sensor node is estimated by combining the individual trust values of each layer. By applying the trust threshold, a sensor node is detected as trusted or malicious. The performance of LB-IDS is evaluated by comparing the results of the three performance parameters such as detection accuracy, false-positive rate, and false-negative rate, with the results of Wang’s scheme. We have implemented jamming attack at the physical layer, back-off manipulation attack at the MAC layer, and sinkhole attack at the network layer using simulations. We have also implemented a cross-layer attack using the simulation where an attacker simultaneously attacks the MAC layer and network layer. Simulation results show that the proposed LB-IDS performs better as compared with Wang’s scheme.

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Trust-based secure clustering in WSN-based intelligent transportation systems

Cited by 141 publications

References 21 publications

Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

Optimal Pricing Strategy of Electric Vehicle Charging Station for Promoting Green Behavior Based on Time and Space Dimensions

Trust based Secure and Energy Efficient Routing using ACO for WSN

LB-IDS: Securing Wireless Sensor Network Using Protocol Layer Trust-Based Intrusion Detection System

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