Unwillingness to pay for privacy: A field experiment

We measure willingness to pay for privacy in a field experiment. Participants were given the choice to buy a maximum of one DVD from one of two online stores. One store consistently required more sensitive personal data than the other, but otherwise the stores were identical. In one treatment, DVDs were one Euro cheaper at the store requesting more personal information, and almost all buyers chose the cheaper store. Surprisingly, in the second treatment when prices were identical, participants bought from both shops equally often. -- Wir messen die Zahlungsbereitschaft für Datenschutz in einem Feldexperiment. Die Teilnehmer konnten maximal eine DVD bei einem von zwei Online-Shops kaufen. Einer der beiden Läden verlangte immer mehr sensitive Daten als der andere, aber abgesehen davon waren die Läden gleich. Im ersten Treatment waren alle DVDs genau einen Euro günstiger bei dem Laden, der mehr sensitive Daten abfragte, und fast alle Käufer wählten diesen günstigeren Laden. In einem zweiten Treatment mit identischen Preisen bei beiden Läden kauften die Teilnehmer überraschenderweise bei beiden Läden gleich häufig.privacy,willingness to pay,field experiments

Unwillingness to Pay for Privacy: A Field Experiment

We measure willingness to pay for privacy in a field experiment. Participants were given the choice to buy a maximum of one DVD from one of two online stores. One store consistently required more sensitive personal data than the other, but otherwise the stores were identical. In one treatment, DVDs were one Euro cheaper at the store requesting more personal information, and almost all buyers chose the cheaper store. Surprisingly, in the second treatment when prices were identical, participants bought from both shops equally often.privacy, willingness to pay, field experiments

Unwillingness to Pay for Privacy: A Field Experiment

We measure willingness to pay for privacy in a field experiment. Participants were given the choice to buy a maximum of one DVD from one of two online stores. One store consistently required more sensitive personal data than the other, but otherwise the stores were identical. In one treatment, DVDs were one Euro cheaper at the store requesting more personal information, and almost all buyers chose the cheaper store. Surprisingly, in the second treatment when prices were identical, participants bought from both shops equally often.privacy, willingness to pay, field experiments

Execution Models for Choreographies and Cryptoprotocols

A choreography describes a transaction in which several principals interact. Since choreographies frequently describe business processes affecting substantial assets, we need a security infrastructure in order to implement them safely. As part of a line of work devoted to generating cryptoprotocols from choreographies, we focus here on the execution models suited to the two levels. We give a strand-style semantics for choreographies, and propose a special execution model in which choreography-level messages are faithfully delivered exactly once. We adapt this model to handle multiparty protocols in which some participants may be compromised. At level of cryptoprotocols, we use the standard Dolev-Yao execution model, with one alteration. Since many implementations use a "nonce cache" to discard multiply delivered messages, we provide a semantics for at-most-once delivery

A data sharing platform for earables research

Ear-worn wearable devices, or earables, are a rapidly emerging sensor platform, with unique opportunities to collect a wide variety of sensor data, and build systems with novel human-computer interaction components. At this point in the development of the field, with projects such as eSense putting hardware in researchers' hands but being limited in reach, the sharing of datasets collected by researchers with the wider community would bring a number of benefits. A central data sharing platform would enable wider participation in earables research and improve the quality of projects, as well as being a vehicle for better data quality and data protection practices. We discuss the considerations behind building such a platform, and propose an architecture that would achieve better privacy-utility trade-offs than many existing data sharing efforts

Effective use of mathematical equations in an online learning environment

Mathematical analysis is an essential tool in the practice of science, technology, engineering, and mathematics, and consequently it is important for students in these subjects to demonstrate effective use of mathematics. In this talk we are interested in supporting the use of mathematical equations in an online learning environment; in particular, we require methods of supporting both the entry and automated marking of mathematical equations, in order to support immediate personalised feedback to the learner

Unwillingness to pay for privacy: a field experiment

"We measure willingness to pay for privacy in a field experiment. Participants were given the choice to buy a maximum of one DVD from one of two online stores. One store consistently required more sensitive personal data than the other, but otherwise the stores were identical. In one treatment, DVDs were one Euro cheaper at the store requesting more personal information, and almost all buyers chose the cheaper store. Surprisingly, in the second treatment when prices were identical, participants bought from both shops equally often." (author's abstract)"Wir messen die Zahlungsbereitschaft für Datenschutz in einem Feldexperiment. Die Teilnehmer konnten maximal eine DVD bei einem von zwei Online-Shops kaufen. Einer der beiden Läden verlangte immer mehr sensitive Daten als der andere, aber abgesehen davon waren die Läden gleich. Im ersten Treatment waren alle DVDs genau einen Euro günstiger bei dem Laden, der mehr sensitive Daten abfragte, und fast alle Käufer wählten diesen günstigeren Laden. In einem zweiten Treatment mit identischen Preisen bei beiden Läden kauften die Teilnehmer überraschenderweise bei beiden Läden gleich häufig." (Autorenreferat

Pudding: Private User Discovery in Anonymity Networks

Anonymity networks allow messaging with metadata privacy, providing better privacy than popular encrypted messaging applications. However, contacting a user on an anonymity network currently requires knowing their public key or similar high-entropy information, as these systems lack a privacy-preserving mechanism for contacting a user via a short, human-readable username. Previous research suggests that this is a barrier to widespread adoption. In this paper we propose Pudding, a novel private user discovery protocol that allows a user to be contacted on an anonymity network knowing only their email address. Our protocol hides contact relationships between users, prevents impersonation, and conceals which usernames are registered on the network. Pudding is Byzantine fault tolerant, remaining available and secure as long as less than one third of servers are crashed, unavailable, or malicious. It can be deployed on Loopix and Nym without changes to the underlying anonymity network protocol, and it supports mobile devices with intermittent network connectivity. We demonstrate the practicality of Pudding with a prototype using the Nym anonymity network. We also formally define the security and privacy goals of our protocol and conduct a thorough analysis to assess its compliance with these definitions.Comment: Accepted at the IEEE Symposium on Security and Privacy (S&P) 202