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In recent years, we have witnessed a rise in the popularity of net- worked hospitality services (NHSs), an online marketplace for short-term peer- to-peer accommodations. Such systems, however, raise significant privacy con- cerns, because service providers such as Airbnb and 9flats can easily collect the precise and personal information of millions of participating hosts and guests through their centralized online platforms. In this paper, we propose PrivateNH, a privacy-enhancing and practical solution that offers anonymity and accountabil- ity for NHS users without relying on any trusted third party. PrivateNH leverages the recent progress of Bitcoin techniques such as Colored Coins and CoinShuffle to generate and maintain anonymous credentials for NHS participants. The cre- dential holders (NHS hosts or guests) can then lease or rent short-term lodging and interact with the service provider in an anonymous and accountable man- ner. An anonymous and secure reputation system is also introduced to establish the trust between unfamiliar hosts and guests in a peer-to-peer fashion. The pro- posed scheme is compatible with the current Bitcoin blockchain system, and its effectiveness and feasibility in NHS scenario are also demonstrated by security analysis and performance evaluation.
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Privacy, Anonymity, and Perceived Risk in Open Collaboration: A Study of Service Providers
Anonymity can enable both healthy online interactions like support-seeking and toxic behaviors like hate speech. How do online service providers balance these threats and opportunities? This two-part qualitative study examines the challenges perceived by open collaboration service providers in allowing anonymous contributions to their projects. We interviewed eleven people familiar with organizational decisions related to privacy and security at five open collaboration projects and followed up with an analysis of public discussions about anonymous contribution to Wikipedia. We contrast our findings with prior work on threats perceived by project volunteers and explore misalignment between policies aiming to serve contributors and the privacy practices of contributors themselves.
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- PAR ID:
- 10098510
- Date Published:
- Journal Name:
- Proceedings of the 2019 CHI Conference on Human Factors in Computing Systems (CHI ’19)
- Page Range / eLocation ID:
- 1 to 12
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3290605.3300901
