Vehicular Platooning to be Secure against Cybersecurity Attacks

Abstract

Vehicular platooning is although not a new concept yet reshaping its core idea with invovlment of autonomous driging in it. vehicle platoon is group of vehicle traveling with small space but no physical connection and negligible relative velocity with each other. Platoon can be formed from different type of vehicles such as truck, bus car etc. In platoon each vehicle has a particular role either it is a leader or follower. All of vehicle participating in platoon have to send message to their predecessor vehicle about their present location, and speed velocity. Along with other different challenges such as its trajectory , string stability , maneuvers, platoon communication suffer from security risks. Security is an essential aspects of wireless communication systems Due to the inherent transmission nature of wireless channels.There is a risk of various types of network attacks,Cyberseurity attacks are most common of them. In this research we will reveal the core idea of cybersecurity attacks in autonomous vehicle platooning.

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“…Today word is leveraged with Artificial Intelligence technology that is playing its role in all paradigm of sciences [1][2][3]. Machine Learning, Deep Learning, Data Science and Data Mining are the most common application areas of AI [4]. Some example application areas of aforementioned techniques is cloud computing, internet of things, autonomous vehicles, zoology and bioinformatics [4][5][6][7].…”

“…Machine Learning, Deep Learning, Data Science and Data Mining are the most common application areas of AI [4]. Some example application areas of aforementioned techniques is cloud computing, internet of things, autonomous vehicles, zoology and bioinformatics [4][5][6][7]. Basic records for approximate geographical distribution Plant and animal species.…”

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“…Today word is leveraged with Artificial Intelligence technology that is playing its role in all paradigm of sciences [1,2]. Machine Learning, Deep Learning, Data Science and Data Mining are the most common application areas of AI [3]. Some example application areas of aforementioned techniques is cloud computing, internet of things, autonomous vehicles, zoology and bioinformatics [3][4][5][6].…”

“…Machine Learning, Deep Learning, Data Science and Data Mining are the most common application areas of AI [3]. Some example application areas of aforementioned techniques is cloud computing, internet of things, autonomous vehicles, zoology and bioinformatics [3][4][5][6]. Basic records for approximate geographical distribution Plant and animal species.…”

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