Title page for etd-0731116-114212


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URN etd-0731116-114212
Author Yen-chih Kuo
Author's Email Address No Public.
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Department Information Management
Year 2016
Semester 1
Degree Master
Type of Document
Language zh-TW.Big5 Chinese
Title Detecting the Accuracy of Highway Incident Warnings in VANETs
Date of Defense 2016-07-25
Page Count 92
Keyword
  • Misbehavior detect
  • Verify alarm
  • Car Cluster
  • Beacon
  • VANET
  • Abstract VANET, so called Vehicular Ad hoc Network, uses cars as nodes to send packages to other cars or road infrastructure. In this basis, VANET can extend lots of car system, and one of them is car alarm system. When the car have strange behavior, car alarm system can sand alarm messages to other cars. However, attackers can spread fake alarm messages to disturb other drivers. The system might also have alarm mistake. So, this study researches the possible situation in the highway, and formulate the perfect misbehavior detect scheme (MDS) to verify the alarm messages. When car alarm system can’t detect the misbehavior car, our system also can assist the car alarm system.
    According to past studies against to detect misbehavior cars, our study integrate them to five dimensions. However, all of the past studies can’t complete contain five dimensions. This study can contain this five dimensions, so that the system can more complete, attackers can’t easily disturb the drivers. In highway, cars can send Beacon messages, which is sent by every second. The Beacon message contains such as car locations, so that the MDS can use the Beacon messages to verify the alarm message. In the real world, not all the cars can send Beacon messages, however, all the past studies assume all the car can send Beacon messages. It may not correct. Our study major for how the rate of not sending Beacon message cars that influences the MDS detection.
    This study use “Car Cluster” to reduce false positive rate, and have more confidence to determine the misbehavior car. This study compares with LEAVE algorithm, proving our scheme have lower false positive rate and have high detect rate.
    Advisory Committee
  • Gu Hsin Lai - chair
  • Hui-Tang Lin - co-chair
  • Chih-Hung Wang - co-chair
  • Chia-Mai Chen - advisor
  • Files
  • etd-0731116-114212.pdf
  • Indicate in-campus at 5 year and off-campus access at 5 year.
    Date of Submission 2016-09-22

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