TC

To stop anonymous tools designed for free speech from being abused by criminals, this project investigates practical solutions to trace back criminals while support free speech for benign users, by exploiting two unique perspectives. First, it utilizes the resource advantages of law enforcement to explore the limitations of anonymous tools. As criminals operated from remote locations usually do not have resources to build large-scale systems, they have to rely on existing anonymous tools with third-party resources to hide their traces.

The security of the national computing infrastructure is critical for consumer confidence, protection of privacy, protection of valuable intellectual property, and even national security. Logic-based approaches to security have been gaining popularity, in part because they provide a precise way to describe and reason about the kinds of complexity found in real systems. Perhaps even more importantly, automated reasoning techniques can be used to assist users in navigating this complexity. Despite the promise of automated reasoning, its use in practical applications is still limited.

Correlation of seemingly innocuous information can create inference chains that tell much more about individuals than they are aware of revealing. However, while media coverage occasionally draws attention to privacy leaks on individual web sites, there is still no comprehensive analysis of the fundamental risks that users face in their online worlds. This project pursues such a study, focusing in particular on the threat of personal, yet publicly available information that can be correlated with modern multimedia retrieval and content analysis technologies.

Biometrics, such as fingerprints, provide a great tool for personalized authentication. While people are usually willing to submit their biometric information to government agencies, they are less likely to do so for commercial companies without a guarantee of privacy protection. This project will have significant societal impact by triggering wide acceptability of large-scale biometrics enabled applications.

Data Protection laws that exempt data that is not individually identifiable have led to an explosion in anonymization research. Unfortunately, how well current de-identification and anonymization techniques control risks to privacy and confidentiality is not well understood. Neither is the usefulness of anonymized data for real-world applications. The project addresses anonymization on three fronts: 1) Textual data, even when explicit identifiers are removed (names, dates, locations), can contain highly identifiable information.