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A Smart Energy-based Source Location Privacy Preservation (SESLPP) Model for IoT-based VANETs
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Vehicle-to-Vehicle (V2V) communication aims to improve road safety by periodic exchange of Hello messages. Nowadays, the Internet of Things (IoT) is widely used to solve city transportation problems by employing multihop-based V2V communication. In IoT-based vehicular ad-hoc networks (VANETs), devices are interconnected with various hardware and software, so the privacy of data, temporal, and location will be at risk due to unauthorized manipulation, especially at intersections in congested urban areas. To address these concerns in IoT-based VANETs, we proposed a Smart Energy-based Source Location Privacy Preservation (SESLPP) technique for sustainable urban city roads (i.e., Intersections). The proposed SESLPP protects the source location privacy while maintaining an accurate reputation based on specific parameters such as trust, speed, distance, and acceleration. A selected node based on these parameters forwards messages and acts as a phantom node to improve the source location privacy within their communication range. The selection of a phantom node is based on a set of parameters, which makes it a multi-criteria decision problem. In this paper, a multi-criteria decision tool known as Analytical Network Process (ANP) has been used for optimal phantom node selection that improves the source location privacy in an urban scenario by considering intersections. We considered the same parameters (trust, speed, distance, and acceleration) that was used for highway scenario with proper adjustment of their values for an urban area (cross-road intersection point). The proposed SESLPP provides an optimal platform for smart city communication networks.
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Wiley Open Access