## 2 Background
### Data Flow Filtering Concept  
In general, during the transmission of information from a source to a destination, the data containing this information are transmitted over a network, generating network traffic or data streams. In today's usually packet-switched networks, the data stream consists of packets [32]. In this paper, we use the term '_data flow_' to refer to a sequence of packets that are transmitted between two participating devices of a network, such as an IoT device and an Internet server, or two IoT devices within the same local network. Technically, the network infrastructure tasked to transport that data could thus prohibit, e.g., block, such flows. For example, preventing the transmission of information from a particular source may be required. This can be reached by filtering the data flow. In this paper, we are interested in blocking information by blocking the transport of network packets that contain such information. Figure 3 shows the idea where the connecting lines stand for network connections, e.g., physical cable infrastructure like in a car (Figure 3a) or wireless network connections like in a home network with a WLAN [33] (Figure 3b). We assume that the process carrying out the filtering is able to see, evaluate, and block the traffic according to rules. In a star-shaped network infrastructure, like the WLAN network of a Smart Home, this function can be located at the WLAN access point (see Figure 4); of course, this could also be distributed [34]. Additionally, other means of filtering could be applied that are more centric to the information, e.g., adding random noise to data or pruning anomalies; this is often also rightly termed 'filtering'. For example in larger IoT deployments such as smart office buildings, there is often building energy management systems (BEMS) that would benefit from trustworthy and 'clean' data as inputs and thus undergoes what is called 'data treatment' [35] or 'data filtering' [35] to increase the data quality. Likewise, but quite to the contrary, the idea of privacy preserving filtering of authenticity-protected energy consumption data [36] adds noise to data to decrease the data quality to a level suitable for both the application and the user's privacy preferences. We briefly touch on the impact of filtering on the data quality in Section 2.6. Moreover, filtering data on the level of network protocols on higher layers within the OSI stack [37], e.g., like filtering and transforming the data's value within messages conforming to the MQTT protocol for increasing Smart Home privacy [38] or within the CAN-Bus of a car [39; 40]. Note, we are not concerned with this data-centric type of filtering in this paper, but with network-centric filtering and the resulting network segmentation. This idea of filtering data within network packets transmitted over a network to increase security is not new and was discussed in the very early days of computer networking [41]. The prevailing concept from [PERSON] and [PERSON] [41] is as follows: a firewall is a device that analyses the network traffic and enforces a set of security policies to block or allow certain data flows. The firewall's goal is to create a barrier between one side of the network, which is deemed to be the inside, and the other side, seen as the outside world. Thus, it prevents unauthorised access to the inside part and thus protects against attacks from the outside. For example, Figure 3 shows the general idea and a possible path the attacker's network packets can travel (_attack vector_). Corresponding to the scenario, the attacker could try to influence the behaviour of the smart car or an IoT device (indicated in Figure 3a,b by a red explosion), or even fully disable the device (indicated in Figure 3b by a red cross). Thinking of the data flow as a continuous stream of packets that is exchanged between two devices over a network connection [42]. Hence, a network firewall should be placed on the path of that data flow so that it has an opportunity to intercept packets.