Christopher J. Riederer

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Most online service providers offer free services to users and in part, these services collect and monetize personally identifiable information (PII), primarily via targeted advertisements. Against this backdrop of economic exploitation of PII, it is vital to understand the value that users put to their own PII. Although studies have tried to discover how(More)
Many popular, professionally-written smartphone apps today prefetch large amounts of network data to improve performance. However, the typical user may not use all of this network data. When a user is on a limited or pay-per-byte cellular data plan, such as when roaming internationally, this prefetching behavior can cost her in overage fees on her cellular(More)
Linking accounts of the same user across datasets – even when personally identifying information is removed or unavailable – is an important open problem studied in many contexts. Beyond many practical applications, (such as cross domain analysis, recommendation, and link prediction), understanding this problem more generally informs us on the privacy(More)
Modern smartphones can create compelling virtual reality (VR) experiences through the use of VR enclosures, devices that encase the phone and project stereoscopic renderings through lenses into the user's eyes. Since the touch screen in such designs is typically hidden inside an enclosure, the main interaction mechanism of the device is not accessible. We(More)
Monetizing personal information is a key economic driver of online industry. End-users are becoming more concerned about their privacy, as evidenced by increased media attention. This paper proposes a mechanism called 'transactional' privacy that can be applied to personal information of users. Users decide what personal information about themselves is(More)
Generations of computer programmers are taught to prefetch network objects in computer science classes. In practice, prefetching can be harmful to the user's wallet when she is on a limited or pay-per-byte cellular data plan. Many popular, professionally-written smartphone apps today prefetch large amounts of network data that the typical user may never(More)
Location data are routinely available to a plethora of mobile apps and third party web services. The resulting datasets are increasingly available to advertisers for targeting and also requested by governmental agencies for law enforcement purposes. While the re-identification risk of such data has been widely reported, the discriminative power of mobility(More)
A practical solution to location privacy should be incrementally deployable. We claim it should hence reconcile the economic value of location to aggregators, usually ignored by prior works, with a user's control over her information. Location information indeed is being collected and used by many mobile services to improve revenues, and this gives rise to(More)
The ubiquitous availability of location data to smartphone apps and online social networks has caused the collection of such information to grow at an unprecedented rate. However, the discriminative power and potential uses of this data collection is not always clear to the end user. In this work, we present FindYou, a web-based application that gives users(More)
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