Privacy-Preserving Ride Sharing Scheme for Autonomous Vehicles

Main Article Content

Shibangsh Chowdhury, Sanjana Mishra, Ujjwal Lokgariwar,Asha R.N.

Abstract

The transport sector is set to undergo an overall change with the advent of autonomous vehicles embedded with artificial intelligence and machine learning. Autonomous vehicles will not only make the road safer but also will improve the efficiency of the modern transport system. Ride sharing is a major gamechanger in the transport industry. Autonomous Vehiclescan make ride sharingpopular, convenientand necessary because it eliminates the need of a driver and will help in recuperating the initial cost of the vehicle. In current scenario, the organization of ride sharing requires the users to disclose sensitive private information not only about the pick-up and drop-off locations but also other details such as name and contact details. In this paper, we propose a scheme to facilitate ride sharing and address the privacy issues that plague down the current industry. The scheme encrypts data using similarity measurement technique to preserve the privacy of the user. The ride sharing route is divided into cells, which is further represented by one bit in a binary vector. Binary vectors are used to represent the trip data of each user.The encryption of the vector data is submitted to a server. The server can measure the similarity of the users’ trip data and find other users who can share rides along the same route without knowing the data. The proposed scheme can facilitate ride sharing without disclosing private information. The scheme is implemented using Visual C on a real map. The measurements from the results have confirmed that the scheme is effective when ride sharing becomes popular and the server needs to organize a large number of rides in short time.

Article Details

How to Cite
, S. C. S. M. U. L. R. “Privacy-Preserving Ride Sharing Scheme for Autonomous Vehicles”. International Journal on Recent and Innovation Trends in Computing and Communication, vol. 6, no. 5, May 2018, pp. 97-105, doi:10.17762/ijritcc.v6i5.1584.
Section
Articles