Abstract
VANET is gaining popularity in recent generation. As increase in the advancement in technology due to the emerging of industry 4.0, VANET is also used in different applications. But the cyber-security attacks are major problem in the VANETs. In recent times, researchers are coming up with various algorithms as a solution to the security problem in the VANETs. In this work, adaptive neuro-fuzzy-based algorithm is introduced. In order to validate results, variables such as detection time, detection ratio, and positive false ratio are used. The outcome of the presented method is finer in comparison to existing methods.
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Shetty, S.R., Manjaiah, D.H. (2023). Adaptive Neuro-Fuzzy Technique for Jamming Detection in VANETs. In: Khanna, A., Gupta, D., Kansal, V., Fortino, G., Hassanien, A.E. (eds) Proceedings of Third Doctoral Symposium on Computational Intelligence . Lecture Notes in Networks and Systems, vol 479. Springer, Singapore. https://doi.org/10.1007/978-981-19-3148-2_49
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DOI: https://doi.org/10.1007/978-981-19-3148-2_49
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