A Fuzzy Logic-Based Control System for Detection and Mitigation of Blackhole Attack in Vehicular Ad Hoc Network

Kumar, Ankit; Pankaj, Dadheech; Beniwal, Mahender Kumar; Agarwal, Basant; Patidar, Pawan

doi:10.1007/978-981-15-0128-9_15

Cited by 8 publications

(4 citation statements)

References 11 publications

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“…It is plainly evident that the majority of the comparable photos have been properly searched, but the images with differing contrast values are separated by a greater distance than the other images. An image with high contrast has more edges than a low contrast image, which accounts for this [32]. The plot between the pictures and the parametric distance is depicted in Figure 14 (right).…”

Section: Search Results For Color Histogram Featurementioning

confidence: 92%

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

Kumar¹,

Singh²,

Raja³

et al. 2021

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In recent years, scholars have found content-based image recovery to be a particularly interesting and exciting field. This field develops quick image recovery algorithms that are very similar to pictures from various data sources. There is currently a lot of space and sources for data storage. Finally, once data sources are obtained, there is just competition for the exact and best result. The result is filtered using the heuristic correlation based on the above features of the photographs. The overall matching scores are calculated by adding all these individual feature ratings. The recommended method will be used to retrieve all images containing the content of the query image. The scores will be used to rate the match. The results of the combined method simulation demonstrate that the strategy is successful. This proposed model will improve the accuracy of search results. This research model, like the other metadata models on the web, is interactive and familiar for searching pictures from huge databases and data sources. This model also has a number of handy features built in to improve precision and efficiency. Although there are a few little mysteries in this model, they must be answered subsequently.

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Section: Search Results For Color Histogram Featurementioning

confidence: 92%

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

Kumar¹,

Singh²,

Raja³

et al. 2021

Self Cite

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“…Fuzzy logic focuses on representing the imprecision of human reasoning for decision making in an imprecise and uncertain environment [95]. In this subsection, trust management models employing fuzzy logic have been presented in detail [96][97][98][99][100]. Guleng et al [96] presented a decentralized trust management framework that employs fuzzy logic to amalgamate a vehicle's direct experience and the recommendations of its peers towards a target vehicle in order to tag the unintended dishonest behavior of the said target vehicle.…”

Section: Fuzzy Logic-based Trust Modelsmentioning

confidence: 99%

“…Kumar et al [98] amalgamated the notions of fuzzy logic and trust to select the best path between two nodes and to identify blackhole attacks. The relationship of vehicles is estimated using trust computations, wherein the proportion of the successfully forwarded messages by the neighbor from the number of messages this neighbor is expected to forward, the ratio of the number of messages received through the neighbor but generated by other nodes to the total count of received messages, and the acknowledgment of the message receipt are aggregated.…”

Section: Fuzzy Logic-based Trust Modelsmentioning

confidence: 99%

A Survey of Trust Management in the Internet of Vehicles

et al. 2021

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Over the past decade, the groundbreaking technological advancements in the Internet of Vehicles (IoV) coupled with the notion of trust have attracted increasing attention from researchers and experts in intelligent transportation systems (ITS), wherein vehicles establish a belief towards their peers in the pursuit of ensuring safe and efficacious traffic flows. Diverse domains have been taking advantage of trust management models in the quest of alleviating diverse insider attacks, wherein messages generated by legitimate users are altered or counterfeited by malicious entities, subsequently, endangering the lives of drivers, passengers, and vulnerable pedestrians. In the course of vehicles forming perceptions towards other participating vehicles, a range of contributing parameters regarding the interactions among these vehicles are accumulated to establish a final opinion towards a target vehicle. The significance of these contributing parameters is typically represented by associating a weighting factor to each contributing attribute. The values assigned to these weighting factors are often set manually, i.e., these values are predefined and do not take into consideration any affecting parameters. Furthermore, a threshold is specified manually that classifies the vehicles into honest and dishonest vehicles relying on the computed trust. Moreover, adversary models as an extension to trust management models in order to tackle the variants of insider attacks are being extensively emphasized in the literature. This paper, therefore, reviews the state of the art in the vehicular trust management focusing on the aforementioned factors such as quantification of weights, quantification of threshold, misbehavior detection, etc. Moreover, an overarching IoV architecture, constituents within the notion of trust, and attacks relating to the IoV have also been presented in addition to open research challenges in the subject domain.

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“…The way in which the measure of confidence is generated, allows us to divide the strategies, structures that contain the actions to be developed, into the types mentioned below we will mention the main characteristics [20] of each types: a) Cluster: This trust scheme uses authentication by means of public keys in the evaluation of a node, these are grouped into clusters which allows a group of nodes to monitor the activity of the equipment directly, the nodes certify the trust of a computer which can be verified with the use of the key and a certificate issued by each neighbour, the nodes which issue trust certificates [21,22] which do not coincide with the evaluation of the Cluster would be considered "malicious" nodes and would lose the possibility of participating in the network [23,24]. b) Social networks: Model based on four components on each computer; Monitor that detects unusual behaviour in the nodes, reputation system that allows the nodes to be qualified acording to their routing or data transmission actions, route manager in charge of selecting the routes they present, and a trusted manager that alerts to the so-called malicious nodes.…”

Section: Trusted Modelsmentioning

confidence: 99%

Evaluation of Trust Algorithm in a Mobile Ad-Hoc Network Using Artificial Engineering

Kowsalya¹

2021

TURCOMAT

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A MANET network is made up of wireless nodes which operate without a defined structure, the arrangement of existing devices does not have any ministerial or control entity . the management tasks are carried out by the teams which are in the network, therefore a MANET network is said to be a managed network. As there is no infrastructure, such as, the bandwidth, availability, input error rate, among others, depend exclusively on the behaviour of the network users. This work presents a functional solution, which decreases the energy consumption in MANET networks, implemented using game theories and genetic algorithms solution. The evaluation of the pay-as-you-go strategy from the modified prisoner dilemma was shown to be an easy to implement and interpret tool for the network equipment. The processes of generation, combination and mutation of strategies demonstrated the in-centive of cooperation in the network, observed in the increase of the average confidence of the nodes, a very high value. The intervention of the protocol with the use of genetic algorithms, demonstrated ot be a form of implementation of solutions for problems of multiple agents, the increase in the evaluation of trust of the nodes was observed, which can be interpreted as a convergence of the nodes to cooperate. The results obtained in the simulations carried out show the functioning of the algorithm implemented and the functionality of the network after its implementation.

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A Fuzzy Logic-Based Control System for Detection and Mitigation of Blackhole Attack in Vehicular Ad Hoc Network

Cited by 8 publications

References 11 publications

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

Design a Framework for Content Based Image Retrieval Using Hybrid Features Analysis

A Survey of Trust Management in the Internet of Vehicles

Evaluation of Trust Algorithm in a Mobile Ad-Hoc Network Using Artificial Engineering

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