# Protecting Sensitive Data in the Information Age: State of the Art and Future Prospects
## 2 Analysis of Modern-Day Smart Services
### Location-Based Services
Such refined data enable a variety of LBS. For instance, they enable the search for stationary objects--e.g., POI in a guide service [32]--or mobile objects--such as drivers or passengers in a ride-sharing service [33]. Smart navigation systems are also made possible by such data. These navigation systems not only take the planned route into consideration but also contextual knowledge such as congestion information provided by other entities [34]. Social networks in particular are increasingly relying on IoT data from other smart services. Here, these data are merged with social media, whereby new insights are gained. Location data play a significant role in this context, as they are not only a key factor in determining the current context of a person but also because they reveal further connections between users [35]. For instance, in location-based social networks, social groups are identified not only based on mutual friends and common interests but also on matching movement patterns [36]. Another cutting-edge use case is the development of autonomous vehicles that do not require any human intervention to find and follow their route [37]. While in the aforementioned use cases, it is only bothersome if the data refinement is inadequate and thus the tracking of entities is not accurate, in autonomous vehicles, this might endanger the physical integrity of humans. Therefore, it is mandatory to delve into the data. Yet, data processed by LBS provide insights into behavioral patterns. Whenever humans can be linked to the data (e.g., the owner of a smart device), this poses a severe privacy threat [38]. The inherent opportunities and privacy threats of LBS can be broken down as follows:  
Figure 1: Examples of Data Refinement Steps for Trajectory Data. Opportunities:  
* The technical ability to locate smart devices (and thus their owners) with high accuracy enables many services, such as navigation services or location-based information services. * The location can also be used to derive a lot of additional information about the data subject, e.g., which places the data subject visits frequently. * If this information is enriched with additional data, such as temporal aspects (How long and when does a data subject stay at a certain place?) or supplementary geographic data (What can be found at that place? ), a very precise profile of the data subject can be created. This makes LBS the foundation of many other context-based services since location is a key parameter in context recognition. Privacy Threats:  
* The current location of a data subject is continuously disclosed by an LBS. This enables long-term surveillance of data subjects. * The data refinement methods described above make it easy to correct even hardware- or software-related inaccuracies, enabling very precise location determination. * Furthermore, LBS can be used to find out much more about a data subject than might initially appear. For instance, they can be used to determine activities and, in the case of long-term use, to draw conclusions about hobbies and social contacts.