## 5 Conclusions and Future Work  
As AR evolves and is applied in fields such as education, healthcare, and entertainment, addressing privacy concerns becomes more critical for its sustainable adoption. This work is on the interplay between AR and user privacy, aiming to identify user preferences and perceptions regarding obfuscation techniques. By understanding user preferences for obfuscation techniques, one can design AR applications that align with user expectations while mitigating privacy risks. In this work, we conducted a comprehensive survey. An analysis of the obtained results led to valuable insights on how users perceived various obfuscation methods in an AR context. Users generally expressed concerns about privacy in AR environments but had varying preferences for obfuscation techniques. Blurring emerged as a popular choice for its ability to maintain visual appeal and preserve information, making it suitable for scenarios in which one prioritizes aesthetics. Masking was regarded as the most secure and trusted method, though its intrusive nature often detracted from the overall user experience. However, pixelation was perceived as a median method across all evaluated criteria. It did not emerge as the best or worst in terms of visual appeal, preserving information, user satisfaction, trust, and security, positioning it centrally within the spectrum of user preferences. This indicates that while pixelation may not excel in any specific category, it offers a balanced approach that could be suitable for general use cases where a moderate level of obfuscation is acceptable. Also, results demonstrated that user familiarity with AR technology influenced the acceptance of obfuscation methods. Although all three methods (blurring, masking, and pixelation) were generally well received, blurring emerged as the most universally accepted technique, particularly among users with higher AR familiarity levels. Pixelation had a medium preference overall and demonstrated consistent user satisfaction across different familiarity levels. Masking showed more variability in user acceptance, indicating that it may not be the optimal choice for all AR contexts, especially for high AR familiarity levels. Demographic factors significantly influenced perceptions of privacy and the acceptance of obfuscation methods. Younger individuals and those with a high-school education tended to have fewer privacy concerns, while older individuals and those with higher education levels exhibited greater awareness and caution. Similarly, professional background emerged as a significant factor, with individuals in the technology, education, and health sectors demonstrating heightened privacy awareness and concern. The methods explored in this study have the potential to be applied in safeguarding sensitive information in shared AR spaces, such as obscuring bystander identities or protecting proprietary data in industrial settings. In future work, we intend to incorporate these results into the automatic selection of obfuscation methods in AR environments, in order to combine the protection of sensitive data with the quality of user experience. To address the limitations highlighted by the small sample size and demographic diversity, future research will focus on expanding the participant pool to enhance the reliability and generalizability of our findings. We will aim to recruit a larger and more diverse sample, allowing for more robust conclusions across different user demographics. Also, some findings can be generalized to other populations and contexts, considering limitations and specific variables. Excessive generalization may lead to premature conclusions, warranting further research. Obfuscation methods can protect data privacy and security but require consideration of ethical and legal implications. Transparent and auditable methods that preserve data integrity must be developed. Exploring different cultural and social contexts can provide more valuable insights into obfuscation methods.