# A Distributed Mix-Context-Based Method for Location Privacy in Road Networks
###### Abstract  
Preserving location privacy is increasingly an essential concern in Vehicular Adhoc Networks (VANETs). Vehicles broadcast beacon messages in an open form that contains information including vehicle identity, speed, location, and other headings. An adversary may track the various locations visited by a vehicle using sensitive information transmitted in beacons such as vehicle identity and location. By matching the vehicle identity used in beacon messages at various locations, an adversary learns the location history of a vehicle. This compromises the privacy of the vehicle driver. In existing research work, pseudonyms are used in place of the actual vehicle identity in the beacons. Pseudonyms should be changed regularly to safeguard the location privacy of vehicles. However, applying simple change in pseudonyms does not always provide location privacy. Existing schemes based on mix zones operate efficiently in higher traffic environments but fail to provide privacy in lower vehicle traffic densities. In this paper, we take the problem of location privacy in diverse vehicle traffic densities. We propose a new Crowd-based Mix Context (CMC) privacy scheme that provides location privacy as well as identity protection in various vehicle traffic densities. The pseudonym changing process utilizes context information of road such as speed, direction and the number of neighbors in transmission range for the anonymisation of vehicles, adaptively updating pseudonyms based on the number of a vehicle neighbors in the vicinity. We conduct formal modeling and specification of the proposed scheme using High-Level Petri Nets (HPLN). Simulation results validate the effectiveness of CMC in terms of location anonymisation, the probability of vehicle traceability, computation time (cost) and effect on vehicular applications. annonymity; formal modeling; location privacy; mix context; pseudonyms; traceability; VANETs +
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The basic architecture of vehicular networks consists of Road Side Units (RSU), On-Board Units (OBU), Event Data Recorders (EDR), various sensors, and navigation systems (such as GPS) [3]. RSUs are a road infrastructure that increase the communication connectivity to vehicles. The OBU is fixed in the vehicle with a temper proof device that protects the cryptographic credentials of vehicles. This is used for wireless communication among vehicles and with infrastructure [4]. An EDR archives various events of vehicles communication during a trip on the road. GPS can be used to provide geographical location, vehicle speed, movement direction, and acceleration for a specific time interval [5]. Obstacles on the road are detected with the aid of radar and sensors. In-vehicle, an omnidirectional antenna is fixed for wireless channel access in the network. The deployment of onboard units permits communication among nearby vehicles and fixed road infrastructure, which make possible three communication models, i.e., Vehicle to Vehicle (V2V), Vehicle to Infrastructure (V2I), and hybrid communication model [3; 6]. In the V2V model, there is no support of infrastructure and vehicles are communicated directly. For data and information gathering, vehicles communicate with road side infrastructure through the V2I model. In the hybrid model, vehicles do not communicate with infrastructure directly but communicate in a single or multihop manner, depending on the transmission range of vehicles. This enables long-distance communication between vehicles in the network. Various wireless technologies are suggested for communication in vehicular networks, such Dedicated Short Range Communication (DSRC), Cellular network, WiMax, WiFi, and VeMAC protocol [6; 7]. Among the existing technologies, DSRC has the potential for use in wide range variety of applications, including collision avoidance which can save thousands of lives and billions of dollars annually [8].