EAGER

Bullying has lasting negative psychological and physical effects on victims, bystanders, and bullies alike; online settings can magnify both the scale and impact of these effects, as anonymity can embolden people to make hostile posts about individuals or groups. This project aims to reduce the prevalence of such posts through the design of active, automated "bystander interventions" in online comment threads.

The explosion in data gathering has greatly exacerbated existing privacy issues in computing systems and created new ones due to the increase in the scale and the scope of available data as well as the advances in the capabilities of computational data analysis. Software professionals typically have no formal training or education on sociotechnical aspects of privacy. As a result, addressing privacy issues raised by a system is frequently an afterthought and/or a matter of compliance-check during the late phases of the system development lifecycle.

This award supports the principal investigator's research in number theory and its cryptographic applications. Number theory serves as the basis for modern cryptography and internet security. The underlying mathematical theories, of elliptic curves and integer factorization, have been studied for centuries. This project includes components of basic research, concerning the relationship between geometry and number theory, as well as foundational research in cryptographic applications, with an eye toward the advent of quantum computers.

The Internet provides a control plane to establish routes to destinations and a data plane to send traffic, and the protocols for both lack authentication. The lack of authentication allows networks to claim ownership of routes to other networks' addresses in order to siphon traffic (prefix hijacking), and allows devices to claim that their traffic came from a different source (source spoofing). These vulnerabilities form the basis for denial-of-service attacks, traffic interception and snooping, Bitcoin theft, and compromises of Tor's anonymity.

Collaborative data analysis has become a necessity and trend in the era of big data. In such collaborative environments, intellectual property protection mechanisms are critical to maintain and encourage research partnerships. Such mechanisms shall protect not only data sources and data analysis algorithms, but also protect data provenance, i.e., data processing history. For example, participating parties may request to secure their access and sharing of various kinds of data products (source, intermediate, and final), processing steps, and their inter-dependencies.