## 2 Background
### Impact of Filtering on Performance and Data Quality  
The goal of filtering for privacy for this paper is to limit the information that is gathered, thereby reducing the negative impact on the privacy of the Smart Home user(s) to a level deemed tolerable by them. Furthermore, the privacy of all individuals affected by the Smart Home's data acquisition should be considered (We here only talk about the filtering applied by the owner of the WLAN network and the devices joining this network. See works like [48] for an idea on how you could protect the privacy of users even in unknown network) The filtering function introduces an overhead that negatively impacts the performance of the networking infrastructure. This overhead arises from two primary factors: the number of rules that have to be evaluated before a match is found and the complexity of each rule. Although the exact impact cannot be quantified in this context, the study [49] by [PERSON] and [PERSON] suggests that filtering at a level that does require that 'the firewall analyzes application commands inside data packets and keeps logs' [49] and that such a firewall '... incurs higher overhead than a simple packet filtering firewall...' [49]. Therefore, we decided to evaluate the impact of packet-level filtering on privacy and security. Figure 5 gives the performance overhead. We implemented our own rule-based firewall with at least the same capabilities as _Bark_ (This is not further elaborated in this paper, as measuring the implementation of filtering was deemed beyond its scope. However, the provided analysis aims to provide indicative values for the performance impact of filtering) and as expected it showed tolerable overheads for bandwidth and latency (We measured the bandwidth using the iperf tool over a period of 60 s and the average latency using the mtr tool over 60 cycles). Overall, 15 configurations were evaluated, with the number of installed network devices ranging from 50 to 700 and varying rule complexities requiring between 50 to 250 checks to evaluate all rules. In an Ethernet-based setup, the results indicate that the performance mainly depends on the number of installed rules, with only a slight increase observed as the number of network devices grows. The latency, measured at a maximum of 3.7 ms for Ethernet with 700 devices and 250 rules can be considered sufficiently low and unlikely to have any noticeable impact, especially in a home network setting. For the WLAN bandwidth, the baseline of the experimental setup was 11.66 Mbit/s, constrained due to the hardware used. In the worst-case scenario with the maximum configuration, the WLAN bandwidth decreased to 10.86 Mbit/s. In our Ethernet setup, the impact on bandwidth becomes clearer: On prototypical hardware (The evaluation was running on a Raspberry Pi 4B with 4 GB of RAM ([[https://www.raspberrypi.org/products/raspberry-pi-4-model-b/](https://www.raspberrypi.org/products/raspberry-pi-4-model-b/)]([https://www.raspberrypi.org/products/raspberry-pi-4-model-b/](https://www.raspberrypi.org/products/raspberry-pi-4-model-b/)) (last accessed: 19 January 2025)) and Linux Kernel 4.19; the WLAN was served via an external USB WiFi dongle based on the Ralink RT5572 chipset) the bandwidth halves to 463 to 451 Mbit/s already in case of only fewer rules and 50 devices as compared to the baseline values of 915 or 940 Mbit/s. In the maximum test with 250 checks within the rules the value decreases to 76 Mbit/s in our prototypical implementation. However, even that value should be sufficiently high for most communication in the local network and is expected to increase if network filtering optimised hardware like in modern routers would be used or other optimisations, e.g., on the order of rules [50], would be facilitated. However, even that value remains sufficiently high for most communication in a local network. Overall, our comparison of different test configurations shows that performance impact depends mostly on the number of rules, while the number of devices shows a comparatively smaller effect.