# Protecting Sensitive Data in the Information Age: State of the Art and Future Prospects
## 2 Analysis of Modern-Day Smart Services
### Image Analysis  
There are also many benefits offered by computer-aided image analysis. While the human eye has physical limitations in terms of detail perceptibility, the capabilities of computational image processing are virtually limitless. Therefore, such data processing techniques are applied in a variety of application domains today. For instance, in the food industry, computer vision can be used to reliably detect foreign objects in food products, medical diagnoses can be supported by the automatic interpretation of computed tomography images, and in the context of defense and homeland security, suspects can be recognized on video recordings [70]. In particular in the field of face recognition, remarkable progress has been made in recent years. While in the early days of this research area in 1964, only a few characteristics of the face could be recognized on images, today, the techniques are so reliable and accurate that they are used in a variety of commercial, industrial, legal, and governmental applications [71]. End-users also come into contact with face recognition services, e.g., in _online social networks_ (_OSNs_) such as _Facebook_ (see [[https://www.facebook.com/](https://www.facebook.com/)]([https://www.facebook.com/](https://www.facebook.com/)), accessed on 30 August 2022) [72]. Here, the so-called _DeepFace_ algorithm is used to identify users on images shared in the network. This algorithm is almost as good as human identification, except that, unlike humans, DeepFace can process large amounts of data in next to no time [73]. Figure 4 illustrates the workflow of face recognition. Initially, all faces on an image must be detected. For instance, characteristic facial features can be identified such as skin color which contrasts with the background, or a model can be trained to detect human faces [74]. Having detected the face, the image needs to be preprocessed, e.g., it has to be cropped to the relevant part of the face. Furthermore, facial landmarks such as the eyes, mouth, and nose have to be marked [75]. For the actual recognition, a comparison with a face database is conducted. To this end, a multinomial classifier is trained using the face database. This classifier can determine with which person from the face database the person on the image has the best match [76]. Various machine learning techniques can be used for this purpose. While in the early days primarily _linear discriminant analysis_ was used, today, _support vector machines_ and _convolutional neural networks_ are used [77]. The application of such image analysis techniques naturally also raises privacy concerns. With today's smartphones, IoT-enabled cameras have become ubiquitous in our everyday lives. Moreover, considering that smartphones can tag captured photos with a time code as well as location information, image analysis can be used to determine not only which people are in a picture together but also when and where that meeting has happened. While this may be intended by the main data subject of the photo, it also affects any bystanders. Due to this potential exposure, measures are needed to restrict such privacy-intrusive scenarios [78]. An additional problem associated with image analysis is the bias in data selection. Such a bias leads to inadequate models, which cause errors in face recognition, resulting in users being incorrectly linked to a photo. Thus, it is important to take measures to prevent bias when preparing the data corpus for training the models [79]. Figure 4: Workflow of a Face Detection and Recognition Based on Machine Learning. The inherent opportunities and privacy threats of image analysis can be broken down as follows:  
Opportunities:  
As social media becomes more and more prevalent in people's lives, image analysis is becoming increasingly relevant for them as well. This allows people to be identified and tagged in images, enabling the automatic linking of people with their social contacts as well as with places and activities.