Density-based Adaptive Wavelet Kernel SVM Model for P2P Traffic Classification

Zong, Xinlu; Wang, Chunzhi; Xu, Hui

doi:10.14257/ijfgcn.2013.6.6.04

Cited by 6 publications

(2 citation statements)

References 21 publications

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“…Their model seems effective in certain situations, but has limitations. Based on similarity, another TM model (Yang, 2013) used the similarity between a node and the data to evaluate the trust level. Although a unique method of similarity was introduced, the technique was not validated.…”

Section: Article Approachmentioning

confidence: 99%

State-of-the-art IoV trust management a meta-synthesis systematic literature review (SLR)

Rehman

Hassan

Hooi

et al. 2020

PeerJ Computer Science

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In the near future, the Internet of Vehicles (IoV) is foreseen to become an inviolable part of smart cities. The integration of vehicular ad hoc networks (VANETs) into the IoV is being driven by the advent of the Internet of Things (IoT) and high-speed communication. However, both the technological and non-technical elements of IoV need to be standardized prior to deployment on the road. This study focuses on trust management (TM) in the IoV/VANETs/ITS (intelligent transport system). Trust has always been important in vehicular networks to ensure safety. A variety of techniques for TM and evaluation have been proposed over the years, yet few comprehensive studies that lay the foundation for the development of a “standard” for TM in IoV have been reported. The motivation behind this study is to examine all the TM models available for vehicular networks to bring together all the techniques from previous studies in this review. The study was carried out using a systematic method in which 31 papers out of 256 research publications were screened. An in-depth analysis of all the TM models was conducted and the strengths and weaknesses of each are highlighted. Considering that solutions based on AI are necessary to meet the requirements of a smart city, our second objective is to analyze the implications of incorporating an AI method based on “context awareness” in a vehicular network. It is evident from mobile ad hoc networks (MANETs) that there is potential for context awareness in ad hoc networks. The findings are expected to contribute significantly to the future formulation of IoVITS standards. In addition, gray areas and open questions for new research dimensions are highlighted.

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Section: Article Approachmentioning

confidence: 99%

State-of-the-art IoV trust management a meta-synthesis systematic literature review (SLR)

Rehman

Hassan

Hooi

et al. 2020

PeerJ Computer Science

View full text Add to dashboard Cite

show abstract

“…This principle is based on the learning machine's generalization error rate which takes the sum of training error rate and VC dimension term as the boundary [11] [12]. In the separable mode for SVM, the first term is zero and the second item is minimized [13]. Therefore, SVM can provide good generalization performance, and this attribute is unique to the SVM.…”

Section: Svm Modelmentioning

confidence: 99%