Nowadays vehicles have been used at a large scale in the modern society. But in many countries the current traffic-safety statistics is very terrifying. Many people are killed and injured in road accident. To reduce this problem government and manufacturers of countries have launched different initiatives like use of safety belt, airbags, antiblocking brake system, and smart vehicular transportation system. Upcoming traffic safety initiatives in smart transportation system depend on information technology and this technology also helps to authenticate and traceable the vehicles in the system. Recently, the smart vehicular system uses different types of networks like VANETs, AI based applications, etc. that aims to provide a safer, coordinated, smooth, and smart mode of transportation. This article focuses on the communication security issues in smart vehicular applications or IoV. Transmitting messages efficiently and honestly among vehicles is the key issues in this system. At present, the communication in smart transportation system is vulnerable to various types of security attacks because it uses an open wireless connection. The different types of attacks are secrecy attack, routing attack, data authenticity attack, attack on authentication besides this in the dense environment, the vehicle may receive multiple messages at the same time. Therefore, how to complete the authentication of multiple messages in a short time is an urgent problem. To address these problems, here we have introduced some technique using the concept of approximation algorithm and linear congruence. The different types of experiments on our technique and their results conform that our scheme is very secure, robust, and efficient for data transmission in smart vehicular or IoV.


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    Title :

    Approximation Algorithm and Linear Congruence: A State-of-Art Approach in Information Security Issues Towards Internet of Vehicles


    Additional title:

    Unmanned Syst. Tech.


    Contributors:


    Publication date :

    2020-09-19


    Size :

    24 pages





    Type of media :

    Article/Chapter (Book)


    Type of material :

    Electronic Resource


    Language :

    English






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