Privacy and Security Management in Intelligent Transportation System
- Authors
- Chavhan, Suresh; Gupta, Deepak; Garg, Sahil; Khanna, Ashish; Choi, Bong Jun; Hossain, M. Shamim
- Issue Date
- Aug-2020
- Publisher
- IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
- Keywords
- Privacy; Urban areas; Cryptography; Task analysis; Security management; Vehicle dynamics; Emergent intelligence; intelligent transportation systems; metropolitan area networks; privacy and security policy; pseudonyms; transport depot staff
- Citation
- IEEE ACCESS, v.8, pp.148677 - 148688
- Journal Title
- IEEE ACCESS
- Volume
- 8
- Start Page
- 148677
- End Page
- 148688
- URI
- http://scholarworks.bwise.kr/ssu/handle/2018.sw.ssu/39641
- DOI
- 10.1109/ACCESS.2020.3015096
- ISSN
- 2169-3536
- 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.
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Collections - College of Information Technology > School of Computer Science and Engineering > 1. Journal Articles
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