## 4 Results and Discussion
### Addressing Research Questions
We used the Kruskal-Wallis test (H) to analyze how the different obfuscation techniques affect user experience across the four different AR contexts. The test aimed to determine if there were statistically significant differences in the perceived adequacy of obfuscation methods between these various AR contexts. Our results revealed that the best privacy protection method depended on the specific situation, while no single obfuscation technique was superior. For the outdoor AR contexts, we obtained the following results:  
* **Bicycle:** People did not strongly prefer any particular technique (H = 3.58; \(p\) = 0.1670), and they had a slight preference for blurring (M = 3.46; \(\sigma\) = 1.35), followed by pixelation (M = 3.15; \(\sigma\) = 1.03) and masking (M = 2.91; \(\sigma\) = 1.55). * **People:** Significant differences were observed (H = 6.00; \(p\) = 0.0499). Blurring (M = 3.46; \(\sigma\) = 1.11) was the most preferred, significantly more so than masking (M = 2.80; \(\sigma\) = 1.44), with pixelation (M = 3.26; \(\sigma\) = 1.04) in the middle. For the indoor AR contexts, we obtained the following results:
* **Document:** Significant differences emerged between the methods (H = 7.91; \(p\) = 0.0191). Pixelation (M = 3.70; \(\sigma\) = 1.19) was the most favored, significantly outperforming masking (M = 2.87; \(\sigma\) = 1.63), and blurring (M = 3.11; \(\sigma\) = 1.27) fell in the middle. * **Screen:** People did not state strong preferences, rating all three techniques--blurring (M = 3.46; \(\sigma\) = 1.03), masking (M = 3.41; \(\sigma\) = 1.47), and pixelation (M = 3.37, \(\sigma\) = 1.16)--similarly (H = 0.18; \(p\) = 0.9120). These findings suggest that the suitability of obfuscation techniques can vary depending on the specific AR context and the type of visual content involved. Figure 7 presents the average rating of the three different methods of obfuscation, masking, pixelation, and blurring, providing comprehensive insight into this question,  
Figure 6: Mean adequacy ratings for masking, pixelation, and blurring techniques in four different AR contexts: outdoor bike, outdoor people, indoor document, and indoor screen. comparing these techniques across the following five metrics: aesthetic, information, satisfaction, security, and trust. Masking was suggested as the most trusted and secure method, but it compromised aesthetic appeal and user satisfaction. Pixelation offered a balanced approach, preserving information while maintaining moderate levels of trust and security, albeit at the cost of aesthetic appeal. Blurring prioritized aesthetic appeal and information retention, but it significantly underperformed in terms of security and trustworthiness. This can indicate that the optimal choice depends on the specific requirements of the application. If prioritizing trust and security is paramount, masking could be the ideal choice. For applications where information preservation and aesthetic appeal are crucial, blurring might be considered. However, pixelation offers a middle ground, balancing information preservation with reasonable levels of trust and security, even though it sacrifices aesthetic appeal. **(RQ3):** Our third research question studied how users' familiarity with AR technology influenced their acceptance of different obfuscation methods. Table 1 presents the mean satisfaction ratings for the blurring, masking, and pixelation methods across different AR familiarity levels (1 = Not at all; 5 = Extremely). The data demonstrate that blurring received consistent preference across both ends of the AR familiarity spectrum, with its highest satisfaction score at AR level 4 (3.75) and its lowest at AR level 1 (2.33). It still stood out with the highest mean score overall (3.45), suggesting that it may be the most generally acceptable technique for users across different  
Figure 7: A comparative analysis of three obfuscation techniques (masking, pixelation, and blurring) based on five key metrics: aesthetic, information, satisfaction, trust, and security.