Users Can Deduce Sensitive Locations Protected by Privacy Zones on Fitness Tracking Apps
Users Can Deduce Sensitive Locations Protected by Privacy Zones on Fitness Tracking Apps
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用户可以在健身追踪应用程序上推断出受隐私区保护的敏感位置
DOI：
10.1145/3491102.3502136
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发表时间：
2022
期刊：
影响因子：
--
通讯作者：
Bates, Adam
中科院分区：
文献类型：
--
作者：
Mink, Jaron;Yuile, Amanda Rose;Pal, Uma;Aviv, Adam J;Bates, Adam
健身跟踪应用程序允许运动员在线记录和分享他们的锻炼，包括他们活动的GPS路线。然而，共享移动数据可能会增加现实世界的隐私和安全风险。一种减轻这种风险的策略是“隐私区”，它隐藏了用户指定的敏感位置的一定半径范围内的锻炼路线。一个紧迫的问题是，隐私区是否是一个有效的威慑常见的攻击者，如自行车小偷，仔细审查在线锻炼活动，以寻找他们的下一个目标。此外，鲜为人知的是用户的隐私区的看法或他们如何融入更广泛的景观可用的隐私precautions.This工作提出了一个在线用户研究（N=603），调查健身跟踪用户的隐私问题，并评估隐私区的功效。参与者首先被问及他们在健身跟踪应用程序方面的隐私行为。接下来，参与者完成了一项互动任务，他们试图推断出受隐私区保护的隐藏位置;我们操纵了与隐私区互动的显示锻炼活动的数量及其大小。最后，参与者被问及关于他们对隐私区的印象和其他隐私保护措施的使用的进一步问题。我们发现，参与者成功地推断出受保护的位置;对于最常见的隐私区大小，当参与者只看到3个活动时，68%的猜测落在隐藏位置的50米范围内。此外，我们发现，与观看1个活动的参与者相比，观看3个活动的参与者对他们在任务中的成功更有信心。综合来看，这些结果表明，即使使用隐私区，用户的隐私敏感位置也存在风险。最后，我们考虑了我们的研究结果对相关隐私功能的影响，并讨论了对健身跟踪用户和服务的建议，以提高健身跟踪器的隐私和安全性。
Fitness tracking applications allow athletes to record and share their exercises online, including GPS routes of their activities. However, sharing mobility data potentially raises real-world privacy and safety risks. One strategy to mitigate that risk is a “Privacy Zone,” which conceals portions of the exercise routes that fall within a certain radius of a user-designated sensitive location. A pressing concern is whether privacy zones are an effective deterrent against common attackers, such as a bike thief that carefully scrutinizes online exercise activities in search of their next target. Further, little is known about user perceptions of privacy zones or how they fit into the broader landscape of available privacy precautions.This work presents an online user study (N=603) that investigates the privacy concerns of fitness tracking users and evaluates the efficacy of privacy zones. Participants were first asked about their privacy behaviors with respect to fitness tracking applications. Next, participants completed an interactive task in which they attempted to deduce hidden locations protected by a privacy zone; we manipulated the number of displayed exercise activities that interacted with the privacy zone, as well as its size. Finally, participants were asked further questions about their impressions of privacy zones and use of other privacy precautions. We found that participants successfully inferred protected locations; for the most common privacy zone size, 68% of guesses fell within 50 meters of the hidden location when participants were shown just 3 activities. Further, we found that participants who viewed 3 activities were more confident about their success in the task compared to participants who viewed 1 activity. Combined, these results indicate that users’ privacy-sensitive locations are at risk even when using a privacy zone. We conclude by considering the implications of our findings on related privacy features and discuss recommendations to fitness tracking users and services to improve the privacy and safety of fitness trackers.
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