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An accurate and efficient collaborative intrusion detection framework to secure vehicular networks

2015

Display Omitted We design and implement an accurate and lightweight intrusion detection framework, called AECFV.AECFV aims to protect the vehicular ad hoc networks (VANETs) against the most dangerous attacks that could occurred on this network.AECFV take into account the VANET's characteristics such as high node's mobility and rapid topology change.AECFV exhibits a high detection rate, low false positive rate, faster attack detection, and lower communication overhead. The advancement of wireless communication leads researchers to develop and conceive the idea of vehicular networks, also known as vehicular ad hoc networks (VANETs). Security in such network is mandatory due to a vital informa…

Vehicular ad hoc networksEngineeringVehicular ad hoc networkOverheadGeneral Computer Sciencebusiness.industryWireless ad hoc networkIntrusion detection systemNode (networking)Detection rateIntrusion detection system[SPI]Engineering Sciences [physics]Control and Systems EngineeringWirelessOverhead (computing)False positive rateElectrical and Electronic EngineeringDetection timebusinessCluster analysisComputer networkVulnerability (computing)Computers & Electrical Engineering
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