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Misbehavior Detection for Position Falsification Attacks in VANETs Using Machine Learning

Ercan, Secil, Ayaida, Marwane, Messai, Nadhir·2022·IEEE Access
DOI 10.1109/access.2021.3136706
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Crossref · 10.1109/access.2021.3136706

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Figures

FIGURE 1 Classification of detection schemes.
FIGURE 1 Classification of detection schemes.CC-BY · From the PDF
FIGURE 2 IDS classification based on the decision mechanism.
FIGURE 2 IDS classification based on the decision mechanism.CC-BY · From the PDF
FIGURE 3 Angle of Arrival and Distance between sender-receiver.
FIGURE 3 Angle of Arrival and Distance between sender-receiver.CC-BY · From the PDF
FIGURE 4 Estimated and declared distance.
FIGURE 4 Estimated and declared distance.CC-BY · From the PDF
Image 5
CC-BY · From the PDF
Image 6
CC-BY · From the PDF
FIGURE 7 Stacking procedure in our case.
FIGURE 7 Stacking procedure in our case.CC-BY · From the PDF
FIGURE 8 Flow of the simulation.
FIGURE 8 Flow of the simulation.CC-BY · From the PDF
TABLE 9. The average performances of the proposed mechanism using the 5 th feature combination and improvements comparing with [44].
TABLE 9. The average performances of the proposed mechanism using the 5 th feature combination and improvements comparing with [44].CC-BY · From the PDF
FIGURE 10 Comparison of detection methods for Attack ID 2.
FIGURE 10 Comparison of detection methods for Attack ID 2.CC-BY · From the PDF
FIGURE 11 Comparison of detection methods for Attack ID 4.
FIGURE 11 Comparison of detection methods for Attack ID 4.CC-BY · From the PDF
FIGURE 12 Comparison of detection methods for Attack ID 8.
FIGURE 12 Comparison of detection methods for Attack ID 8.CC-BY · From the PDF
FIGURE 13 Comparison of detection methods for Attack ID 16.
FIGURE 13 Comparison of detection methods for Attack ID 16.CC-BY · From the PDF
FIGURE 14 Proposed IDS for different traffic densities.
FIGURE 14 Proposed IDS for different traffic densities.CC-BY · From the PDF
Image 15
CC-BY · From the PDF
Image 16
CC-BY · From the PDF
Image 17
CC-BY · From the PDF

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Research works printed but not linked: 49

  1. 10.23919/ECC.2019.8795704 · DOI
  2. 10.1016/S1005-8885(15)60676-8 · DOI
  3. 10.1016/j.adhoc.2016.10.011 · DOI
  4. 10.1109/LCN48667.2020.9314803 · DOI
  5. 10.1007/978-3-540-45248-5_10 · DOI
  6. 10.1016/j.adhoc.2017.03.006 · DOI
  7. 10.1016/j.future.2017.12.008 · DOI
  8. 10.1109/SaCoNeT.2018.8585454 · DOI
  9. 10.1109/IWCMC.2019.8766572 · DOI
  10. 10.1016/j.adhoc.2019.01.010 · DOI
  11. 10.1109/ICCSP.2016.7754429 · DOI
  12. 10.1109/JSEN.2020.3021731 · DOI
  13. 10.1016/j.vehcom.2014.05.001 · DOI
  14. 10.1002/dac.2566 · DOI
  15. 10.1109/ECS.2015.7124850 · DOI
  16. 10.1109/ICCC.2015.7432979 · DOI
  17. 10.1145/2307888.2307902 · DOI
  18. 10.1002/dac.3106 · DOI
  19. 10.1016/j.procs.2015.01.006 · DOI
  20. 10.1016/j.vehcom.2019.100186 · DOI
  21. 10.1109/IVS.2018.8500485 · DOI
  22. 10.1109/DSN.2017.10 · DOI
  23. 10.1109/ICDCSW.2009.48 · DOI
  24. 10.1007/978-3-030-01701-9_18 · DOI
  25. Maglaras, 2015, A novel distributed intrusion detection system for vehicular ad hoc networks, Int. J. Adv. Comput. Sci. Appl., 6, 3676
  26. 10.1109/VTC2021-Spring51267.2021.9448878 · DOI
  27. 10.1109/ACCESS.2018.2875678 · DOI
  28. 10.1109/VNC48660.2019.9062831 · DOI
  29. 10.1109/TVT.2020.2984878 · DOI
  30. 10.1007/978-981-15-3750-9_6 · DOI
  31. 10.1016/j.vehcom.2017.12.003 · DOI
  32. 10.1016/j.eswa.2015.12.006 · DOI
  33. 10.1109/ICFCC.2010.5497798 · DOI
  34. 10.1109/AINS.2017.8270417 · DOI
  35. 10.1109/ACCESS.2019.2950805 · DOI
  36. 10.3390/rs11232852 · DOI
  37. 10.1016/j.cose.2018.06.008 · DOI
  38. 10.1109/APNOMS.2017.8094172 · DOI
  39. 10.3390/electronics9091411 · DOI
  40. 10.1145/3317549.3323406 · DOI
  41. 10.1007/978-981-13-7561-3_13 · DOI
  42. 10.1109/ICMLA.2018.00091 · DOI
  43. 10.1109/HST47167.2019.9032989 · DOI
  44. 10.1109/ICC.2019.8761300 · DOI · Paper page
  45. 10.1016/j.proeng.2011.08.162 · DOI
  46. 10.1109/JIOT.2021.3098051 · DOI
  47. 10.1016/j.cose.2016.11.004 · DOI
  48. 10.1023/A:I0I0933404324 · DOI
  49. 10.1109/JIOT.2020.3034621 · DOI

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Metadata

Authors
Ercan, S., Ayaida, M., & Messai, N.
ORCID
Venue
IEEE Access
Publisher
Institute of Electrical and Electronics Engineers (IEEE)
Published
2022
Volume
10
Pages
1893-1904
ISSN
2169-3536
DOI
10.1109/access.2021.3136706
Cited by
109
References
0
Licence
creativecommons.org/licenses/by/4.0/legalcode (vor)
Funders
  • C-Roads France
  • European Commission from the CINEA Agency within the 2015 CEF Transport Programme. The statements made herein are solely the responsibility of the authors (2015-FRTM-0378-S)

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