A security framework for QaaS model in intelligent transportation systems

Abstract

Recent advances in the development of intelligent transportation systems (ITSs) impose complex services that utilize Query-as-a-Service Model in ITS microsystems. Such model is vulnerable to a vast range of security threats such as Man-in-the-Middle attacks. Intelligent sensors and microsystems provide important systems-level functionalities to smart cities applications, which enhance data acquisition and system control services. This paper proposes a communication framework that handles intrusion threats to intelligent sensors during the data acquisition and service provision phases. The contributions of this research are: (1) Proposing a reliable Query-as-a-Service communication model based on Fog computing architecture, (2) Proposing communication protocols that preserve the integrity of exchanged data through intelligent sensors, and (3) Providing a security analysis based on the mobile nature of vehicles in ITS microsystems. Our proposed methodology is a data-driven one, in which entities exchange data models instead of the data itself, thus, minimizing the communication overhead and providing a smart way to tolerate misinformation. We have conducted experiments to analyze the impact of failure rate and the size of exchanged data on our proposed framework. In addition, the computational cost has been tested against the amount of communicated data reports. The results indicated that the proposed framework showed high performance in terms of the impact of data granularity on the failure rate and computational cost. Our proposed methodology achieved 89.6% detection rate, 3.5% false-detection rate, and <0.02 probability of query failure. Accordingly, our proposed framework overcomes the major limitations of traditional cloud-based model.