Adaptive Neuro-Fuzzy Technique for Jamming Detection in VANETs

被引：1
作者：
Shetty, Shubha R. [1 ]
Manjaiah, D. H. [1 ]
机构：
[1] Mangalore Univ, Dept Comp Sci, Mangalore, India
来源：
PROCEEDINGS OF THIRD DOCTORAL SYMPOSIUM ON COMPUTATIONAL INTELLIGENCE, DOSCI 2022 | 2023年 / 479卷
关键词：
VANET; Jamming attacks; ANFIS; Detection rates; OPTIMIZATION; ALGORITHM;
D O I：
10.1007/978-981-19-3148-2_49
中图分类号：
TP18 [人工智能理论];
学科分类号：
081104 ; 0812 ; 0835 ; 1405 ;
摘要：
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.
引用
收藏
页码：571 / 580
页数：10
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