[1][2] This technique is usually integrated into applications in various environments to minimize the disclosure of private information when users request location-based service.
Since the database server does not receive the accurate location information, a set including the satisfying solution would be sent back to the user.
[8] The overall idea of preserving location privacy is to introduce enough noise and quantization to reduce the chances of successful attacks.
In order to meet user's requirements for location privacy in the process of data transportation, researchers have been exploring and investigating models to address the disclosure of private information.
[3] The minimal information sharing model is introduced to use cryptographic techniques to perform join and intersection operations.
[2] Several methods have been investigated to enhance the performances of location-preserving techniques, such as location perturbation and the report of landmark objects.
[3] Spatial and temporal cloaking refers to the wrong or imprecise location and time reported to the service providers, instead of the exact information.
[1][12] For example, one of the methods to achieve this is by replacing the correct network addresses with fake-IDs before the information are forward to the service provider.
[16] Third, the location anonymizer may lead to a performance bottleneck when a large number of requests are presented and required to be cloaked.
[15][16] This is because the location anonymizer is responsible for maintaining the number of users in a region in order to provide an acceptable level of service quality.
[15] In a distributed environment, users anonymize their location information through fixed communication infrastructures, such as base stations.
[3] However, the complexity of the data structure which is used to anonymize the location could result in difficulties when applying this mechanism to highly dynamic location-based mobile applications.
[19] In this environment, peers have to trust each other and work together, since their location information would be reported to each other when a cloaked area is constructed to achieve the desired K-anonymity during the requesting for location-based services.
[16] In mobile devices, Global Positioning System (GPS) is the most commonly used component to provide location information.
[8] Minimum area size refers to the smallest region expanded from the exact location point which satisfies the specific privacy requirements.
This might result in an inefficient cloaked area since the space where the user could potentially reside is smaller compared with the situation of the same level of K-anonymity, yet people are more scattered from each other.
With the popularity and development of global positioning system (GPS) and wireless communication,[16] location-based information services have been in high growth in recent years.
[3] Snapshot queries generally require the report of an exact location at a specific time, such as “where is the nearest gas station?” while continuous queries need the tracking of location during a period of time, such as “constantly reporting the nearby gas stations.”[3] With the advancement of global positioning systems and the development of wireless communication which are introduced in the extensive use of location-based applications, high risks have been placed on user privacy.
Since the a series of cloaked areas are reported, with the advancing technological performances, a correlation could be generated between the blurred regions.
Some mechanisms have been proposed to either address the privacy-preserving issues in both of the two environments simultaneously or concentrate on fulfilling each privacy requirement respectively.
For example, tools such as cryptography, anonymity, obfuscation and caching have been proposed, discussed, and tested to better preserve user privacy.
Second, the ability of attackers requires a more in-depth consideration and investigation according to the advancement of technology such as machine learning and its connection with social relations, particularly the share of information online.
Software bugs, configuration errors at the trusted-third-party and malicious administrators could expose private user data under high risks.
[6] Based on a study from 2010, two-thirds of all the trusted-third-party applications in the Android market are considered to be suspicious towards sensitive information.
Under this situation, even adversaries do not have physical contact with the mobile device, users’ personal information would still under risks of being disclosed.
[4][31][32] Policy approaches have also been discussed in recent years which intend to revise relevant guidelines or propose new regulations to better manage location-based service applications.
The current technology state does not have a sufficiently aligned policies and legal environment, and there are efforts from both academia and industry trying to address this issue.
[35] GSMA published a new privacy guideline, and some mobile companies in Europe have signed it and started to implement it so that users would have a better understanding of the information recorded and analyzed when using location-based services.
The suspect tried to suppress the evidence based on the tracking device used during the monitoring process, but the court denied this.
Therefore, law enforcement agents are required to secure a warrant before obtaining vehicle's location information with the GPS tracking devices.