Understand and Measure Privacy

This project examines three properties of underground cybercrime communities: 1) profitability, 2) connectivity, 3) and sustainability. It identifies qualitative and quantitative metrics for these properties as well as discusses the relative effectiveness of distinct operationalization of these metrics under different levels of data granularity. The goal is to develop metrics that provide meaning indicators even when data is limited. for example, if public posts are available but not private messages between individual cybercriminals.

Cloud computing has emerged as one of the most successful computing models in recent years. However, lack of accountability and non-compliance with data protection regulations have prevented major users such as business, healthcare, and defense organizations from utilizing clouds for sensitive data and applications. Due to the lack of information about cloud internals and the inability to perform trustworthy audits, today's clouds are often not used in regulated industries, preventing their widespread adoption.

The goal of our work is to (a) capture people's expectations and surprises in using mobile apps in a scalable manner, and to (b) summarize these perceptions in a simple format to help people make better trust decisions. Our main idea is analyzing privacy in the form of people's expectations about what an app will and won't do, focusing on where an app breaks people's expectations. We are building an App Scanner that combines automated scanning techniques with crowdsourcing.

This research project studies a new area of research - exposure detection - that is at the intersection of data mining, security, and natural language processing. Exposure detection refers to discovering components/attributes of a user's public profile that reduce the user's privacy. To help the public understand the privacy risks of sharing certain information on the web, this research project focuses on developing efficient algorithms for modeling how an adversary learns information using incomplete and schemaless public data sources.

Cloud computing offers many benefits to users, including increased availability and flexibility of resources, and efficiency of equipment. However, privacy concerns are becoming a major barrier to users transitioning to cloud computing. The privilege design of existing cloud platforms creates great challenges in ensuring the trustworthiness of cloud by granting too much power to the cloud administrators, who could launch serious insider attacks by abusing the administrative privileges.