Privacy and Security Management in Intelligent Transportation System

Suresh Chavhan,Bong Jun Choi,Sahil Garg,M Shamim Hossain,Ashish Khanna,Deepak Gupta

doi:10.1109/access.2020.3015096

Abstract

Metropolitan transportation is a dynamic and non-linear complex system. In such a system, there are possibilities of altering, monitoring, forging, and accessing private, public, and resource information of depot staff and communicating agents by unauthorized agencies the metropolitan area. Existing solutions for the management of security and privacy of communicating agents in an intelligent public transportation system (IPTS) do not adapt to the dynamic occurrence of real-time event information. Therefore, existing solutions are insufficient to address the randomness and other characteristics pertaining to a non-linear complex system such as an intelligent transport system (ITS). To this end, in this article, we propose a privacy and security management scheme for ITS depot staff in a metropolitan area. This scheme provides privacy and security management in the transportation industry during the exchange of information regarding vehicle allocation, dispatch, revocation, financial, and maintenance. Absence of such an aforementioned scheme leads to anomalies such as impersonation of genuine staff and malicious and greedy staff. We use the emergent intelligence (EI) technique to collect, analyze, and share information, and take dynamic decisions during the security and privacy management of the depot staff in transport industries. The EI technique provides autonomy, flexibility, adaptiveness, robustness, self-organization, and evolution to address the randomness and behavior of a non-linear complex system pertaining to the transportation system in metropolitan areas. The proposed scheme is implemented using the Crypto++ package, and the results indicate that the scheme efficiently manages the security and privacy in transportation industries in metropolitan areas.

Highlights

Metropolitan areas which include urban areas, satellite cities, rural areas, etc., are highly congested
It records the misbehavior events and creates a misbehavior of legitimate staff report (MSR), i.e., MSR = < MIS, Poli, IDx >, where MIS is the misbehavior information, Poli is the policy of i-th level and IDx is the identity of misbehaving legitimate staff, x
In this article, we proposed a novel security and privacy management scheme for the intelligent public transportation industry in a metropolitan area

Summary

INTRODUCTION

Metropolitan areas which include urban areas, satellite cities, rural areas, etc., are highly congested. Owing to the advancement of various information and communication technologies (ICTs) [3], [4] and high penetration of their deployment, a greater threat of observing and analyzing communication entities by third parties arises This problem can be mitigated by using privacy preservation techniques such as anonymity, mutual authentication, and cryptography [8], [11]. The broadcast group key management (BGKM) scheme [20] was proposed for managing the key, wherein an attribute-based access control policy preserves the user’s identity attributes while sharing documents in an untrusted cloud storage This approach encrypts and decrypts the document if it satisfies the policy and keys. Such keys cannot preserve and disclose privacy as required, and are not efficient for distributed environments To this end, in this article, we propose a privacy and security management scheme for supporting IPTS depots in metropolitan areas using an emergent intelligence (EI) technique.

SYSTEM MODEL

TRANSPORT DEPOT STAFF PRIVACY PRESERVATION MODEL

TRANSPORT DEPOT STAFF REVOCATION

PERFORMANCE ANALYSIS

CONCLUSION