## 5 Interpretation of Results with Respect to Usability  
In this section, we focus on the combination of our technical measurements with studies of user behaviour while browsing the web. The aim is to reason about the influence of the latency that we measured on user acceptance. We already introduced critical latency values gained from experimental research (cf. Section 2). According to this related work, in particular in Table 1, we assume that user tolerance of waiting for web-page requests decreases after 2 s; it falls sharply within the interval between 7 s and 15 s, and ends with 50 s when the user stops waiting. In our opinion, the related research conducted by [PERSON] _et al_. [33] is best suited for our experiment due to its empirical grounding and most recent data in comparison to the other studies. However, we extend these experimentally measured lab results [33] with results stated by users from our own survey [27]. Figure 9 shows four different scenarios with cancelation rates over time. The curve labeled \"Nah without FB\" is referencing the \"first-attempt waiting\" scenario of [PERSON] in which the user is confronted with a broken link while not getting any feedback from the web browser [33]. Here, an important metric is introduced: the percentage of users who abandoned the wait during the time interval specified. We adopt this _cancelation rate_ as a good indicator for the user's waiting tolerance in our setting. The curve labeled \"Nah with Feedback\" is referencing the first attempt waiting scenario in which the user is confronted with a broken link while getting feedback in form of a progress bar from the web  
Figure 9: Cancellation Rate of Different Scenarios. browser [33]. The other two scenarios are derived from our own survey and show stated tolerated waiting times for normal and anonymous web browsing. Those two cancelation rate curves indicate that people surfing anonymously have a higher tolerance in terms of latency. Nevertheless, the gap between the curves is small: The correlation is 0.989, the medians are 18.556 and 21.096 s, respectively. There are 948 data points. The maximum difference D between the cumulative distributions according to the Kolmogorov-Smirnov comparison is: 0.0854, with a corresponding p-value of: 0.002 (statistically significant at 0.5% level). Furthermore, we note that our survey results also confirmed the results of Nah's lab experiments. In order to reason about expected cancelation rates for browsing the web via Tor, we map our technical latency results to corresponding user cancelation rates. On the technical side, we apply our core and page latency measurements for both direct connections and connections over Tor. Page latency, estimated by the applying the measured factor 2.4 to core latency, increases the median of core latency for HTTP requests via Tor from 13.36 s to 32.06 s. The median of HTTP requests without Tor increases from 1.72 s to 4.13 s.  
?From a usability perspective, we are provided with stated as well as experimentally measured user cancelation rates. As stated cancelation rates, we have statements for direct connection and anonymized connection. Experimental cancelation rates can be divided in those with and without feedback. Out of the \(4\times 4\) possible combinations, Table 4 shows the meaningful mappings. The results from the lab experiment with feedback can be mapped to page latency because the user is given feedback during loading of the page (the page builds up stepwise). The lab experiment without feedback should be mapped to core latency because the user gets no detailed visual progress feedback until first data is retrieved. In Figures 10-13, we present our mappings of technical latency results (LT) and corresponding user cancelation rates (CR) of Figure 9. Each of the four figures describes a different type of cancelation rate and the meaningful mappings for technical latency (from Table 4).