LEADER 04425nam 22007095 450 001 9910337467703321 005 20250820220205.0 010 $a3-030-01731-1 024 7 $a10.1007/978-3-030-01731-6 035 $a(CKB)4100000007110839 035 $a(MiAaPQ)EBC5583595 035 $a(DE-He213)978-3-030-01731-6 035 $a(Au-PeEL)EBL5583595 035 $a(CaPaEBR)ebr11636389 035 $a(OCoLC)1066185916 035 $a(PPN)23146293X 035 $a(EXLCZ)994100000007110839 100 $a20181029d2019 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aLearning-based VANET Communication and Security Techniques /$fby Liang Xiao, Weihua Zhuang, Sheng Zhou, Cailian Chen 205 $a1st ed. 2019. 210 1$aCham :$cSpringer International Publishing :$cImprint: Springer,$d2019. 215 $a1 online resource (140 pages) 225 1 $aWireless Networks,$x2366-1445 311 08$a3-030-01730-3 327 $a1 Introduction -- 2 Learning-based Rogue Edge Detection in VANETs with Ambient Radio Signals -- 3 Learning While Offloading: Multi-armed Bandit Based Task Offloading in Vehicular Edge Computing Networks -- 4 Intelligent Network Access System for Vehicular Real-time Service Provisioning -- 5 UAV Relay in VANETs Against Smart Jamming with Reinforcement Learning -- 6 Conclusion and Future Work. 330 $aThis timely book provides broad coverage of vehicular ad-hoc network (VANET) issues, such as security, and network selection. Machine learning based methods are applied to solve these issues. This book also includes four rigorously refereed chapters from prominent international researchers working in this subject area. The material serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to VANET communication and security related issues. This book will also help readers understand how to use machine learning to address the security and communication challenges in VANETs. Vehicular ad-hoc networks (VANETs) support vehicle-to-vehicle communications and vehicle-to-infrastructure communications to improve the transmission security, help build unmanned-driving, and support booming applications of onboard units (OBUs). The high mobility of OBUs and the large-scale dynamic network with fixed roadside units (RSUs) make the VANET vulnerable to jamming. The anti-jamming communication of VANETs can be significantly improved by using unmanned aerial vehicles (UAVs) to relay the OBU message. UAVs help relay the OBU message to improve the signal-to-interference-plus-noise-ratio of the OBU signals, and thus reduce the bit-error-rate of the OBU message, especially if the serving RSUs are blocked by jammers and/or interference, which is also demonstrated in this book. This book serves as a useful reference for researchers, graduate students, and practitioners seeking solutions to VANET communication and security related issues. 410 0$aWireless Networks,$x2366-1445 606 $aWireless communication systems 606 $aMobile communication systems 606 $aData protection 606 $aArtificial intelligence 606 $aTelecommunication 606 $aWireless and Mobile Communication 606 $aData and Information Security 606 $aArtificial Intelligence 606 $aCommunications Engineering, Networks 615 0$aWireless communication systems. 615 0$aMobile communication systems. 615 0$aData protection. 615 0$aArtificial intelligence. 615 0$aTelecommunication. 615 14$aWireless and Mobile Communication. 615 24$aData and Information Security. 615 24$aArtificial Intelligence. 615 24$aCommunications Engineering, Networks. 676 $a004.6 700 $aXiao$b Liang$4aut$4http://id.loc.gov/vocabulary/relators/aut$0911797 702 $aZhuang$b Weihua$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aZhou$b Sheng$4aut$4http://id.loc.gov/vocabulary/relators/aut 702 $aChen$b Cailian$4aut$4http://id.loc.gov/vocabulary/relators/aut 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9910337467703321 996 $aLearning-based VANET Communication and Security Techniques$92041878 997 $aUNINA