Trust and anonymity are both desirable properties on the Internet. However, online services and users often have to make the trade off between trust and anonymity due to the lack of usable frameworks for achieving them both. We propose Opaak, a practical anonymous authentication framework. Opaak enables its users to establish identities with different online services while ensuring that these identities cannot be linked with each other or their real identity. In addition, Opaak allows online service providers to control the rate at which users utilize their services while preserving their anonymity. Hence, allowing the service providers to prevent abuse in the form of spam or Sybil attacks, which are prevalent in such online services that offer anonymity. Opaak leverages the mobile phone as a scarce resource combined with anonymous credentials in order to provide these features. We target two kinds of applications for Opaak and identify their requirements in order to achieve both trust and anonymity. We develop efficient protocols for these applications based on anonymous credentials. In addition, we design an architecture that facilitates integration with existing mobile and web applications and allows application developers to transparently utilize our protocols. We implement a prototype on Android and evaluate its performance to demonstrate the practicality of our approach.

Anyone within range of an 802.11 wireless network ("Wi-Fi") can use free software to collect the unencrypted web traffic of others on the network. However, many Wi-Fi users are completely unaware of the risk that this creates. This work aims to improve users' awareness about what they expose to others on Wi-Fi networks and provide them with some control. Our system, the Wi-Fi Privacy Ticker, displays information about the exposure of sensitive terms that are sent to and from a user's computer and prevents the unencrypted transmission of terms from the user's computer that she has identified as highly sensitive. In a three-week field study with 17 participants, we found that the Wi-Fi Privacy Ticker improved participants' awareness of the circumstances in which their personal information is transmitted. We show that this heightened awareness contributed to changes in their behavior while on Wi-Fi.

We describe the design and implementation of Privacy Oracle, a system that reports on application leaks of user information via the network traffic that they send. Privacy Oracle treats each application as a black box, without access to either its internal structure or communication protocols. This means that it can be used over a broad range of applications and information leaks (i.e., not only Web traffic or credit card numbers). To accomplish this, we develop a differential testing technique in which perturbations in the application inputs are mapped to perturbations in the application outputs to discover likely leaks; we leverage alignment algorithms from computational biology to find high quality mappings between different byte-sequences efficiently. Privacy Oracle includes this technique and a virtual machine-based testing system. To evaluate it, we tested 26 popular applications, including system and file utilities, media players, and IM clients. We found that Privacy Oracle discovered many small and previously undisclosed information leaks. In several cases, these are leaks of directly identifying information that are regularly sent in the clear (without end-to-end encryption) and which could make users vulnerable to tracking by third parties or providers.