FRINK Linked Data Fragments server

Matches in SemOpenAlex for { <https://semopenalex.org/work/W4200538043> ?p ?o ?g. }

• W4200538043 endingPage "16" @default.
• W4200538043 startingPage "1" @default.
• W4200538043 abstract "With the increasing development of wireless communication technology and Vehicular Ad hoc Network (VANET), as well as the continuous popularization of various sensors, Mobile Crowdsensing (MCS) paradigm has been widely concerned in the field of transportation. As a currently popular data sensing way, it mainly relies on wireless sensing devices to complete large-scale and complex sensing tasks. However, since vehicles are highly mobile in this scenario and the sensing system is open, that is, any vehicle equipped with sensing device can join the system, the credibility of all participating vehicles cannot be guaranteed. In addition, malicious users will upload false data in the sensing system, which makes the sensing data not meet the needs of the sensing tasks and will threaten traffic safety in some serious cases. There are many solutions to the above problems, such as cryptography, incentive mechanism, and reputation mechanisms. Unfortunately, although these schemes guaranteed the credibility of users, they did not give much thought to the reliability of data. In addition, some schemes brought a lot of overhead, some used a centralized server management architecture, and some were not suitable for the scenario of VANET. Therefore, this paper firstly proposes the MCS-VANET architecture-based blockchain, which consists of participating vehicles (PVs), road side units (RSUs), cloud server (CS), and the blockchain (BC), and then designs a malicious user detection scheme composed of three phases. In the data collecting phase, to reduce the data uploading overhead, data aggregation and machine learning technologies are combined by fully considering the historical reputation value of PVs, and the proportion of data uploading is determined based on the historical data quality evaluation result of PVs. In the data quality evaluation phase, a new reputation computational model is proposed to effectively evaluate the sensing data, which contains four indicators: the reputation history of PVs, the data unbiasedness, the leadership of PVs, and the spatial force of PVs. In the reputation updating phase, to achieve the effective change of reputation values, the logistic model function curve is introduced and the result of the reputation updating is stored in the blockchain for security publicity. Finally, on real datasets, the feasibility and effectiveness of our proposed scheme are demonstrated through the experimental simulation and security analysis. Compared with existing schemes, the proposed scheme not only reduces the cost of data uploading but also has better performance." @default.
• W4200538043 created "2021-12-31" @default.
• W4200538043 creator A5006355718 @default.
• W4200538043 creator A5019056615 @default.
• W4200538043 creator A5033547500 @default.
• W4200538043 creator A5066294478 @default.
• W4200538043 creator A5070430221 @default.
• W4200538043 creator A5081049185 @default.
• W4200538043 date "2021-12-21" @default.
• W4200538043 modified "2023-10-18" @default.
• W4200538043 title "An Efficient and Secure Malicious User Detection Scheme Based on Reputation Mechanism for Mobile Crowdsensing VANET" @default.
• W4200538043 cites W1901616594 @default.
• W4200538043 cites W1982467666 @default.
• W4200538043 cites W1991922063 @default.
• W4200538043 cites W2032596903 @default.
• W4200538043 cites W2064164188 @default.
• W4200538043 cites W2078862823 @default.
• W4200538043 cites W2125826911 @default.
• W4200538043 cites W2316899877 @default.
• W4200538043 cites W2342845836 @default.
• W4200538043 cites W2505353160 @default.
• W4200538043 cites W2587108042 @default.
• W4200538043 cites W2724474800 @default.
• W4200538043 cites W2757189075 @default.
• W4200538043 cites W2796856437 @default.
• W4200538043 cites W2803109435 @default.
• W4200538043 cites W2848791610 @default.
• W4200538043 cites W2898176384 @default.
• W4200538043 cites W2901485330 @default.
• W4200538043 cites W2906042702 @default.
• W4200538043 cites W2908265534 @default.
• W4200538043 cites W2943584607 @default.
• W4200538043 cites W2949043202 @default.
• W4200538043 cites W2984191096 @default.
• W4200538043 cites W3157891444 @default.
• W4200538043 doi "https://doi.org/10.1155/2021/5302257" @default.
• W4200538043 hasPublicationYear "2021" @default.
• W4200538043 type Work @default.
• W4200538043 citedByCount "3" @default.
• W4200538043 countsByYear W42005380432022 @default.
• W4200538043 countsByYear W42005380432023 @default.
• W4200538043 crossrefType "journal-article" @default.
• W4200538043 hasAuthorship W4200538043A5006355718 @default.
• W4200538043 hasAuthorship W4200538043A5019056615 @default.
• W4200538043 hasAuthorship W4200538043A5033547500 @default.
• W4200538043 hasAuthorship W4200538043A5066294478 @default.
• W4200538043 hasAuthorship W4200538043A5070430221 @default.
• W4200538043 hasAuthorship W4200538043A5081049185 @default.
• W4200538043 hasBestOaLocation W42005380431 @default.
• W4200538043 hasConcept C111919701 @default.
• W4200538043 hasConcept C127413603 @default.
• W4200538043 hasConcept C144024400 @default.
• W4200538043 hasConcept C147176958 @default.
• W4200538043 hasConcept C192448918 @default.
• W4200538043 hasConcept C2779960059 @default.
• W4200538043 hasConcept C31258907 @default.
• W4200538043 hasConcept C36289849 @default.
• W4200538043 hasConcept C38652104 @default.
• W4200538043 hasConcept C41008148 @default.
• W4200538043 hasConcept C47796450 @default.
• W4200538043 hasConcept C48798503 @default.
• W4200538043 hasConcept C555944384 @default.
• W4200538043 hasConcept C71901391 @default.
• W4200538043 hasConcept C76155785 @default.
• W4200538043 hasConcept C79974875 @default.
• W4200538043 hasConcept C94523657 @default.
• W4200538043 hasConceptScore W4200538043C111919701 @default.
• W4200538043 hasConceptScore W4200538043C127413603 @default.
• W4200538043 hasConceptScore W4200538043C144024400 @default.
• W4200538043 hasConceptScore W4200538043C147176958 @default.
• W4200538043 hasConceptScore W4200538043C192448918 @default.
• W4200538043 hasConceptScore W4200538043C2779960059 @default.
• W4200538043 hasConceptScore W4200538043C31258907 @default.
• W4200538043 hasConceptScore W4200538043C36289849 @default.
• W4200538043 hasConceptScore W4200538043C38652104 @default.
• W4200538043 hasConceptScore W4200538043C41008148 @default.
• W4200538043 hasConceptScore W4200538043C47796450 @default.
• W4200538043 hasConceptScore W4200538043C48798503 @default.
• W4200538043 hasConceptScore W4200538043C555944384 @default.
• W4200538043 hasConceptScore W4200538043C71901391 @default.
• W4200538043 hasConceptScore W4200538043C76155785 @default.
• W4200538043 hasConceptScore W4200538043C79974875 @default.
• W4200538043 hasConceptScore W4200538043C94523657 @default.
• W4200538043 hasFunder F4320321001 @default.
• W4200538043 hasLocation W42005380431 @default.
• W4200538043 hasLocation W42005380432 @default.
• W4200538043 hasOpenAccess W4200538043 @default.
• W4200538043 hasPrimaryLocation W42005380431 @default.
• W4200538043 hasRelatedWork W2027636740 @default.
• W4200538043 hasRelatedWork W2061231656 @default.
• W4200538043 hasRelatedWork W2062688728 @default.
• W4200538043 hasRelatedWork W2771454953 @default.
• W4200538043 hasRelatedWork W3046762796 @default.
• W4200538043 hasRelatedWork W3202102306 @default.
• W4200538043 hasRelatedWork W4231650586 @default.
• W4200538043 hasRelatedWork W4327774248 @default.
• W4200538043 hasRelatedWork W45347327 @default.
• W4200538043 hasRelatedWork W2998294818 @default.

• next