# Security Challenges of Location Privacy in VANETs and State-of-the-Art Solutions: A Survey
## 3 Related Work
### Location Privacy Preserving Schemes
#### 3.2.3 Obfuscation-Based Approaches  
Obfuscation strategies can make tracking hard by reducing the precision of position data and growing the time interval between messages received by OBU. This method works well in situations where LBS do not need precise location information to provide an appropriate level of quality of service (QOS). Reference [50] proposed an information theoretic method that uses Markov chains to induce certain pre-calculated location errors. The sum of error is estimated when checking that the LBS are usable, but the position specificity is decreased, and a new nickname is given. Selection of pseudonyms is often randomized by first sorting out all likely pseudonyms. The method mentioned represented the entire traffic population, assuming that the user had very little knowledge of the number and characteristics of the other users available. The location of each user shall be recorded along with a calculated error correlated with a certain probability.  
The Probability Distribution Function (PDF) can present the location and velocity of each consumer. The purpose of the obfuscation feature is to modify the PDF for all users' changes to the victim's PDF source remain unclear to the offender. The aim of this obfuscation function is to make unaware of the user's historical data and so it does not overlap with it. User locations are known as independent and uniformly distributed variables, based on Markov chains to capture their dependency over time [50]. Possible locations are related to the number of Markov-row states, Whitman, and so on [51]. Three new blotting techniques, namely N-Rand, N-Mix and N-Dispersion algorithms, were introduced. By comparing the average distance, maximum distance and minimum distance between the original position and the obfuscated direction, we evaluated the efficiency of these algorithms. Another recent work carried out by [11] used privacy with the aid of the Circle Based Dummy Generation (CBDG) algorithm while using a trustworthy third party. The proposed solution benefits both from obfuscation and anonymization techniques by sharing location information between neighboring vehicles in a two-step verification process [12]. Many other parallel efforts [34] have used a variety of obfuscation mechanisms to hide accurate location data while providing an appropriate quality of service. Upon evaluating the pros and cons of the obfuscation method, the algorithm can be repeatedly applied at the OBU, so its implementation is considered easy. Under light traffic conditions, even if it is relatively noisy, the attacker can monitor the target vehicle within the range set by the noise level of the system.  
Nevertheless, crowded urban areas and road, highway settings contribute to the confusion and obscure certain users' position. This scheme provides a personalized service extension for the customer, since the TA will identify the user uniquely. The compensation provided, though, cannot provide position related facilities. The positioning accuracy does not indicate the user's exact position.